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1101.2405
|
Improved Peak Cancellation for PAPR Reduction in OFDM Systems
|
cs.IT math.IT
|
This letter presents an improved peak cancellation (PC) scheme for
peak-to-average power ratio (PAPR) reduction in orthogonal frequency division
multiplexing (OFDM) systems. The main idea is based on a serial peak
cancellation (SPC) mode for alleviating the peak regrowth of the conventional
schemes. Based on the SPC mode, two particular algorithms are developed with
different tradeoff between PAPR and computational complexity. Simulation shows
that the proposed scheme has a better tradeoff among PAPR, complexity and
signal distortion than the conventional schemes.
|
1101.2416
|
Decentralized Formation Control Part I: Geometric Aspects
|
math.OC cs.MA cs.SY
|
In this paper, we develop new methods for the analysis of decentralized
control systems and we apply them to formation control problems. The basic
set-up consists of a system with multiple agents corresponding to the nodes of
a graph whose edges encode the information that is available to the agents. We
address the question of whether the information flow defined by the graph is
sufficient for the agents to accomplish a given task. Formation control is
concerned with problems in which agents are required to stabilize at a given
distance from other agents. In this context, the graph of a formation encodes
both the information flow and the distance constraints, by fixing the lengths
of the edges. A formation is said to be rigid if it cannot be continuously
deformed with the distance constraints satisfied; a formation is minimally
rigid if no distance constraint can be omitted without the formation losing its
rigidity. Hence, the graph underlying minimally rigid formation provides just
enough constraints to yield a rigid formation. An open question we will settle
is whether the information flow afforded by a minimally rigid graph is
sufficient to insure global stability. We show that the answer is negative in
the case of directed information flow. In this first part, we establish basic
properties of formation control in the plane. Formations and the associated
control problems are defined modulo rigid transformations. This fact has strong
implications on the geometry of the space of formations and on the feedback
laws, since they need to respect this invariance. We study both aspects here.
We show that the space of frameworks of n agents is CP(n-2) x (0,\infty). We
then illustrate how the non-trivial topology of this space relates to the
parametrization of the formation by inter-agent distances.
|
1101.2421
|
Decentralized Formation Control Part II: Algebraic aspects of
information flow and singularities
|
math.OC cs.MA cs.SY
|
Given an ensemble of autonomous agents and a task to achieve cooperatively,
how much do the agents need to know about the state of the ensemble and about
the task in order to achieve it? We introduce new methods to understand these
aspects of decentralized control. Precisely, we introduce a framework to
capture what agents with partial information can achieve by cooperating and
illustrate its use by deriving results about global stabilization of directed
formations. This framework underscores the need to differentiate the knowledge
an agent has about the task to accomplish from the knowledge an agent has about
the current state of the system. The control of directed formations has proven
to be more difficult than initially thought, as is exemplified by the lack of
global result for formations with n \geq 4 agents. We established in part I
that the space of planar formations has a non-trivial global topology. We
propose here an extension of the notion of global stability which, because it
acknowledges this non-trivial topology, can be applied to the study of
formation control. We then develop a framework that reduces the question of
whether feedback with partial information can stabilize the system to whether
two sets of functions intersect. We apply this framework to the study of a
directed formation with n = 4 agents and show that the agents do not have
enough information to implement locally stabilizing feedback laws.
Additionally, we show that feedback laws that respect the information flow
cannot stabilize a target configuration without stabilizing other, unwanted
configurations.
|
1101.2427
|
Content-Based Filtering for Video Sharing Social Networks
|
cs.CV cs.SI
|
In this paper we compare the use of several features in the task of content
filtering for video social networks, a very challenging task, not only because
the unwanted content is related to very high-level semantic concepts (e.g.,
pornography, violence, etc.) but also because videos from social networks are
extremely assorted, preventing the use of constrained a priori information. We
propose a simple method, able to combine diverse evidence, coming from
different features and various video elements (entire video, shots, frames,
keyframes, etc.). We evaluate our method in three social network applications,
related to the detection of unwanted content - pornographic videos, violent
videos, and videos posted to artificially manipulate popularity scores. Using
challenging test databases, we show that this simple scheme is able to obtain
good results, provided that adequate features are chosen. Moreover, we
establish a representation using codebooks of spatiotemporal local descriptors
as critical to the success of the method in all three contexts. This is
consequential, since the state-of-the-art still relies heavily on static
features for the tasks addressed.
|
1101.2435
|
Networks with arbitrary edge multiplicities
|
physics.soc-ph cs.SI physics.data-an
|
One of the main characteristics of real-world networks is their large
clustering. Clustering is one aspect of a more general but much less studied
structural organization of networks, i.e. edge multiplicity, defined as the
number of triangles in which edges, rather than vertices, participate. Here we
show that the multiplicity distribution of real networks is in many cases
scale-free, and in general very broad. Thus, besides the fact that in real
networks the number of edges attached to vertices often has a scale-free
distribution, we find that the number of triangles attached to edges can have a
scale-free distribution as well. We show that current models, even when they
generate clustered networks, systematically fail to reproduce the observed
multiplicity distributions. We therefore propose a generalized model that can
reproduce networks with arbitrary distributions of vertex degrees and edge
multiplicities, and study many of its properties analytically.
|
1101.2478
|
Delay and Power-Optimal Control in Multi-Class Queueing Systems
|
math.OC cs.SY
|
We consider optimizing average queueing delay and average power consumption
in a nonpreemptive multi-class M/G/1 queue with dynamic power control that
affects instantaneous service rates. Four problems are studied: (1) satisfying
per-class average delay constraints; (2) minimizing a separable convex function
of average delays subject to per-class delay constraints; (3) minimizing
average power consumption subject to per-class delay constraints; (4)
minimizing a separable convex function of average delays subject to an average
power constraint. Combining an achievable region approach in queueing systems
and the Lyapunov optimization theory suitable for optimizing dynamic systems
with time average constraints, we propose a unified framework to solve the
above problems. The solutions are variants of dynamic $c\mu$ rules, and
implement weighted priority policies in every busy period, where weights are
determined by past queueing delays in all job classes. Our solutions require
limited statistical knowledge of arrivals and service times, and no statistical
knowledge is needed in the first problem. Overall, we provide a new set of
tools for stochastic optimization and control over multi-class queueing systems
with time average constraints.
|
1101.2483
|
On Achievability of Gaussian Interference Channel Capacity to within One
Bit
|
cs.IT math.IT
|
In the earlier version of this paper, it was wrongly claimed that
time-sharing is required to achieve the capacity region of the Gaussian
interference channel to within one bit, especially at corner points. The flaw
in the argument of the earlier version lies in fixing the decoding paradigm for
a fixed common/private message splitting encoding strategy. More specifically,
the additional constraints (7b) and (7d) in the earlier version arise if we
force the common messages to be always decoded at unintended receivers.
However, (7b) and (7d) can be eliminated by allowing the decoders to ignore
unintended common messages, particularly at corner points of the rate region,
without resorting to time-sharing at the transmit side, as suggested in the
earlier version. For these reasons, our earlier claim is invalid.
|
1101.2491
|
A Review of Research on Devnagari Character Recognition
|
cs.CV
|
English Character Recognition (CR) has been extensively studied in the last
half century and progressed to a level, sufficient to produce technology driven
applications. But same is not the case for Indian languages which are
complicated in terms of structure and computations. Rapidly growing
computational power may enable the implementation of Indic CR methodologies.
Digital document processing is gaining popularity for application to office and
library automation, bank and postal services, publishing houses and
communication technology. Devnagari being the national language of India,
spoken by more than 500 million people, should be given special attention so
that document retrieval and analysis of rich ancient and modern Indian
literature can be effectively done. This article is intended to serve as a
guide and update for the readers, working in the Devnagari Optical Character
Recognition (DOCR) area. An overview of DOCR systems is presented and the
available DOCR techniques are reviewed. The current status of DOCR is discussed
and directions for future research are suggested.
|
1101.2516
|
Maximum Rate of Unitary-Weight, Single-Symbol Decodable STBCs
|
cs.IT math.IT
|
It is well known that the Space-time Block Codes (STBCs) from Complex
orthogonal designs (CODs) are single-symbol decodable/symbol-by-symbol
decodable (SSD). The weight matrices of the square CODs are all unitary and
obtainable from the unitary matrix representations of Clifford Algebras when
the number of transmit antennas $n$ is a power of 2. The rate of the square
CODs for $n = 2^a$ has been shown to be $\frac{a+1}{2^a}$ complex symbols per
channel use. However, SSD codes having unitary-weight matrices need not be
CODs, an example being the Minimum-Decoding-Complexity STBCs from
Quasi-Orthogonal Designs. In this paper, an achievable upper bound on the rate
of any unitary-weight SSD code is derived to be $\frac{a}{2^{a-1}}$ complex
symbols per channel use for $2^a$ antennas, and this upper bound is larger than
that of the CODs. By way of code construction, the interrelationship between
the weight matrices of unitary-weight SSD codes is studied. Also, the coding
gain of all unitary-weight SSD codes is proved to be the same for QAM
constellations and conditions that are necessary for unitary-weight SSD codes
to achieve full transmit diversity and optimum coding gain are presented.
|
1101.2524
|
Generalized Silver Codes
|
cs.IT math.IT
|
For an $n_t$ transmit, $n_r$ receive antenna system ($n_t \times n_r$
system), a {\it{full-rate}} space time block code (STBC) transmits $n_{min} =
min(n_t,n_r)$ complex symbols per channel use. The well known Golden code is an
example of a full-rate, full-diversity STBC for 2 transmit antennas. Its
ML-decoding complexity is of the order of $M^{2.5}$ for square $M$-QAM. The
Silver code for 2 transmit antennas has all the desirable properties of the
Golden code except its coding gain, but offers lower ML-decoding complexity of
the order of $M^2$. Importantly, the slight loss in coding gain is negligible
compared to the advantage it offers in terms of lowering the ML-decoding
complexity. For higher number of transmit antennas, the best known codes are
the Perfect codes, which are full-rate, full-diversity, information lossless
codes (for $n_r \geq n_t$) but have a high ML-decoding complexity of the order
of $M^{n_tn_{min}}$ (for $n_r < n_t$, the punctured Perfect codes are
considered). In this paper, a scheme to obtain full-rate STBCs for $2^a$
transmit antennas and any $n_r$ with reduced ML-decoding complexity of the
order of $M^{n_t(n_{min}-(3/4))-0.5}$, is presented. The codes constructed are
also information lossless for $n_r \geq n_t$, like the Perfect codes and allow
higher mutual information than the comparable punctured Perfect codes for $n_r
< n_t$. These codes are referred to as the {\it generalized Silver codes},
since they enjoy the same desirable properties as the comparable Perfect codes
(except possibly the coding gain) with lower ML-decoding complexity, analogous
to the Silver-Golden codes for 2 transmit antennas. Simulation results of the
symbol error rates for 4 and 8 transmit antennas show that the generalized
Silver codes match the punctured Perfect codes in error performance while
offering lower ML-decoding complexity.
|
1101.2533
|
A Low ML-decoding Complexity, Full-diversity, Full-rate MIMO Precoder
|
cs.IT math.IT
|
Precoding for multiple-input, multiple-output (MIMO) antenna systems is
considered with perfect channel knowledge available at both the transmitter and
the receiver. For 2 transmit antennas and QAM constellations, an approximately
optimal (with respect to the minimum Euclidean distance between points in the
received signal space) real-valued precoder based on the singular value
decomposition (SVD) of the channel is proposed, and it is shown to offer a
maximum-likelihood (ML)-decoding complexity of $\mathcal{O}(\sqrt{M})$ for
square $M$-QAM. The proposed precoder is obtainable easily for arbitrary QAM
constellations, unlike the known complex-valued optimal precoder by Collin et
al. for 2 transmit antennas, which is in existence for 4-QAM alone with an
ML-decoding complexity of $\mathcal{O}(M\sqrt{M})$ (M=4) and is extremely hard
to obtain for larger QAM constellations. The proposed precoder's loss in error
performance for 4-QAM in comparison with the complex-valued optimal precoder is
only marginal. Our precoding scheme is extended to higher number of transmit
antennas on the lines of the E-$d_{min}$ precoder for 4-QAM by Vrigneau et al.
which is an extension of the complex-valued optimal precoder for 4-QAM.
Compared with the recently proposed $X-$ and $Y-$precoders, the error
performance of our precoder is significantly better. It is shown that our
precoder provides full-diversity for QAM constellations and this is supported
by simulation plots of the word error probability for $2\times2$, $4\times4$
and $8\times8$ systems.
|
1101.2549
|
An Estimation of the Shortest and Largest Average Path Length in Graphs
of Given Density
|
physics.soc-ph cs.SI
|
Many real world networks (graphs) are observed to be 'small worlds', i.e.,
the average path length among nodes is small. On the other hand, it is somewhat
unclear what other average path length values networks can produce. In
particular, it is not known what the maximum and the minimum average path
length values are. In this paper we provide a lower estimation for the shortest
average path length (l) values in connected networks, and the largest possible
average path length values in networks with given size and density. To the
latter end, we construct a special family of graphs and calculate their average
path lengths. We also demonstrate the correctness of our estimation by
simulations.
|
1101.2575
|
Errata list for "Error Control Coding" by Lin and Costello
|
cs.IT math.IT
|
This document lists some errors found in the second edition of Error Control
Coding by Shu Lin and Daniel J. Costello, Jr.
|
1101.2613
|
A Novel Probabilistic Pruning Approach to Speed Up Similarity Queries in
Uncertain Databases
|
cs.DB
|
In this paper, we propose a novel, effective and efficient probabilistic
pruning criterion for probabilistic similarity queries on uncertain data. Our
approach supports a general uncertainty model using continuous probabilistic
density functions to describe the (possibly correlated) uncertain attributes of
objects. In a nutshell, the problem to be solved is to compute the PDF of the
random variable denoted by the probabilistic domination count: Given an
uncertain database object B, an uncertain reference object R and a set D of
uncertain database objects in a multi-dimensional space, the probabilistic
domination count denotes the number of uncertain objects in D that are closer
to R than B. This domination count can be used to answer a wide range of
probabilistic similarity queries. Specifically, we propose a novel geometric
pruning filter and introduce an iterative filter-refinement strategy for
conservatively and progressively estimating the probabilistic domination count
in an efficient way while keeping correctness according to the possible world
semantics. In an experimental evaluation, we show that our proposed technique
allows to acquire tight probability bounds for the probabilistic domination
count quickly, even for large uncertain databases.
|
1101.2678
|
Parallelization Strategies for Ant Colony Optimisation on GPUs
|
cs.DC cs.MA
|
Ant Colony Optimisation (ACO) is an effective population-based meta-heuristic
for the solution of a wide variety of problems. As a population-based
algorithm, its computation is intrinsically massively parallel, and it is
there- fore theoretically well-suited for implementation on Graphics Processing
Units (GPUs). The ACO algorithm comprises two main stages: Tour construction
and Pheromone update. The former has been previously implemented on the GPU,
using a task-based parallelism approach. However, up until now, the latter has
always been implemented on the CPU. In this paper, we discuss several
parallelisation strategies for both stages of the ACO algorithm on the GPU. We
propose an alternative data-based parallelism scheme for Tour construction,
which fits better on the GPU architecture. We also describe novel GPU
programming strategies for the Pheromone update stage. Our results show a total
speed-up exceeding 28x for the Tour construction stage, and 20x for Pheromone
update, and suggest that ACO is a potentially fruitful area for future research
in the GPU domain.
|
1101.2713
|
Matched Filtering from Limited Frequency Samples
|
cs.IT math.IT
|
In this paper, we study a simple correlation-based strategy for estimating
the unknown delay and amplitude of a signal based on a small number of noisy,
randomly chosen frequency-domain samples. We model the output of this
"compressive matched filter" as a random process whose mean equals the scaled,
shifted autocorrelation function of the template signal. Using tools from the
theory of empirical processes, we prove that the expected maximum deviation of
this process from its mean decreases sharply as the number of measurements
increases, and we also derive a probabilistic tail bound on the maximum
deviation. Putting all of this together, we bound the minimum number of
measurements required to guarantee that the empirical maximum of this random
process occurs sufficiently close to the true peak of its mean function. We
conclude that for broad classes of signals, this compressive matched filter
will successfully estimate the unknown delay (with high probability, and within
a prescribed tolerance) using a number of random frequency-domain samples that
scales inversely with the signal-to-noise ratio and only logarithmically in the
in the observation bandwidth and the possible range of delays.
|
1101.2719
|
CSSF MIMO RADAR: Low-Complexity Compressive Sensing Based MIMO Radar
That Uses Step Frequency
|
cs.IT math.IT
|
A new approach is proposed, namely CSSF MIMO radar, which applies the
technique of step frequency (SF) to compressive sensing (CS) based multi-input
multi-output (MIMO) radar. The proposed approach enables high resolution range,
angle and Doppler estimation, while transmitting narrowband pulses. The problem
of joint angle-Doppler-range estimation is first formulated to fit the CS
framework, i.e., as an L1 optimization problem. Direct solution of this problem
entails high complexity as it employs a basis matrix whose construction
requires discretization of the angle-Doppler-range space. Since high resolution
requires fine space discretization, the complexity of joint range, angle and
Doppler estimation can be prohibitively high. For the case of slowly moving
targets, a technique is proposed that achieves significant complexity reduction
by successively estimating angle-range and Doppler in a decoupled fashion and
by employing initial estimates obtained via matched filtering to further reduce
the space that needs to be digitized. Numerical results show that the
combination of CS and SF results in a MIMO radar system that has superior
resolution and requires far less data as compared to a system that uses a
matched filter with SF.
|
1101.2721
|
Optimized data sharing in multicell MIMO with finite backhaul capacity
|
cs.IT math.IT
|
This paper addresses cooperation in a multicell environment where base
stations (BSs) wish to jointly serve multiple users, under a
constrained-capacity backhaul. We point out that for finite backhaul capacity a
trade-off between sharing user data, which allows for full MIMO cooperation,
and not doing so, which reduces the setup to an interference channel but also
requires less overhead, emerges. We optimize this trade-off by formulating a
rate splitting approach in which non-shared data (private to each transmitter)
and shared data are superposed. We derive the corresponding achievable rate
region and obtain the optimal beamforming design for both shared and private
symbols. We show how the capacity of the backhaul can be used to determine how
much of the user data is worth sharing across multiple BSs, particularly
depending on how strong the interference is.
|
1101.2728
|
Index Coding and Error Correction
|
cs.IT math.IT
|
A problem of index coding with side information was first considered by Y.
Birk and T. Kol (IEEE INFOCOM, 1998). In the present work, a generalization of
index coding scheme, where transmitted symbols are subject to errors, is
studied. Error-correcting methods for such a scheme, and their parameters, are
investigated. In particular, the following question is discussed: given the
side information hypergraph of index coding scheme and the maximal number of
erroneous symbols $\delta$, what is the shortest length of a linear index code,
such that every receiver is able to recover the required information? This
question turns out to be a generalization of the problem of finding a
shortest-length error-correcting code with a prescribed error-correcting
capability in the classical coding theory. The Singleton bound and two other
bounds, referred to as the $\alpha$-bound and the $\kappa$-bound, for the
optimal length of a linear error-correcting index code (ECIC) are established.
For large alphabets, a construction based on concatenation of an optimal index
code with an MDS classical code, is shown to attain the Singleton bound. For
smaller alphabets, however, this construction may not be optimal. A random
construction is also analyzed. It yields another inexplicit bound on the length
of an optimal linear ECIC. Finally, the decoding of linear ECIC's is discussed.
The syndrome decoding is shown to output the exact message if the weight of the
error vector is less or equal to the error-correcting capability of the
corresponding ECIC.
|
1101.2785
|
Multiplexed Model Predictive Control
|
cs.SY math.OC
|
This paper proposes a form of MPC in which the control variables are moved
asynchronously. This contrasts with most MIMO control schemes, which assume
that all variables are updated simultaneously. MPC outperforms other control
strategies through its ability to deal with constraints. This requires on-line
optimization, hence computational complexity can become an issue when applying
MPC to complex systems with fast response times. The multiplexed MPC scheme
described in this paper solves the MPC problem for each subsystem sequentially,
and updates subsystem controls as soon as the solution is available, thus
distributing the control moves over a complete update cycle. The resulting
computational speed-up allows faster response to disturbances, which may result
in improved performance, despite finding sub-optimal solutions to the original
problem.
|
1101.2804
|
Aging in language dynamics
|
physics.soc-ph cond-mat.stat-mech cs.CL cs.MA
|
Human languages evolve continuously, and a puzzling problem is how to
reconcile the apparent robustness of most of the deep linguistic structures we
use with the evidence that they undergo possibly slow, yet ceaseless, changes.
Is the state in which we observe languages today closer to what would be a
dynamical attractor with statistically stationary properties or rather closer
to a non-steady state slowly evolving in time? Here we address this question in
the framework of the emergence of shared linguistic categories in a population
of individuals interacting through language games. The observed emerging
asymptotic categorization, which has been previously tested - with success -
against experimental data from human languages, corresponds to a metastable
state where global shifts are always possible but progressively more unlikely
and the response properties depend on the age of the system. This aging
mechanism exhibits striking quantitative analogies to what is observed in the
statistical mechanics of glassy systems. We argue that this can be a general
scenario in language dynamics where shared linguistic conventions would not
emerge as attractors, but rather as metastable states.
|
1101.2834
|
Subjective Collaborative Filtering
|
cs.IR cs.SI
|
We present an item-based approach for collaborative filtering. We determine a
list of recommended items for a user by considering their previous purchases.
Additionally other features of the users could be considered such as page
views, search queries, etc... In particular we address the problem of
efficiently comparing items. Our algorithm can efficiently approximate an
estimate of the similarity between two items. As measure of similarity we use
an approximation of the Jaccard similarity that can be computed by constant
time operations and one bitwise OR. Moreover we improve the accuracy of the
similarity by introducing the concept of user preference for a given product,
which both takes into account multiple purchases and purchases of related
items. The product of the user preference and the Jaccard measure (or its
approximation) is used as a score for deciding whether a given product has to
be recommended.
|
1101.2926
|
Convergence to consensus in multiagent systems and the lengths of
inter-communication intervals
|
math.OC cs.MA math.DS
|
A theorem on (partial) convergence to consensus of multiagent systems is
presented. It is proven with tools studying the convergence properties of
products of row stochastic matrices with positive diagonals which are infinite
to the left. Thus, it can be seen as a switching linear system in discrete
time. It is further shown that the result is strictly more general than results
of Moreau (IEEE Transactions on Automatic Control, vol. 50, no. 2, 2005),
although Moreau's results are formulated for generally nonlinear updating maps.
This is shown by demonstrating the existence of an appropriate switching linear
system which mimics the nonlinear updating maps. Further on, an example system
is given for which convergence to consensus can be shown by using the theorem.
In this system the lengths of intercommunication intervals in the switching
communication topology grows without bound. This makes other theorems not
applicable.
|
1101.2937
|
A Deterministic Polynomial--Time Algorithm for Constructing a Multicast
Coding Scheme for Linear Deterministic Relay Networks
|
cs.IT math.IT
|
We propose a new way to construct a multicast coding scheme for linear
deterministic relay networks. Our construction can be regarded as a
generalization of the well-known multicast network coding scheme of Jaggi et
al. to linear deterministic relay networks and is based on the notion of flow
for a unicast session that was introduced by the authors in earlier work. We
present randomized and deterministic polynomial--time versions of our algorithm
and show that for a network with $g$ destinations, our deterministic algorithm
can achieve the capacity in $\left\lceil \log(g+1)\right\rceil $ uses of the
network.
|
1101.2985
|
Resequencing: A Method for Conforming to Conventions for Sharing Credits
Among Multiple Authors
|
cs.DL cs.CY cs.IR
|
Devising an appropriate scheme that assigns the weights to share credits
among multiple authors of a paper is a challenging task. This challenge comes
from the fact that different types of conventions might be followed among
different research discipline or research groups. In this paper, we discuss
that for the purpose of evaluating the quality of research produced by authors,
one can resequence either authors or weights and can apply a weight assignment
policy which the evaluator deems fit for the particular research discipline or
research group.
|
1101.2987
|
Support vector machines/relevance vector machine for remote sensing
classification: A review
|
cs.CV cs.LG
|
Kernel-based machine learning algorithms are based on mapping data from the
original input feature space to a kernel feature space of higher dimensionality
to solve a linear problem in that space. Over the last decade, kernel based
classification and regression approaches such as support vector machines have
widely been used in remote sensing as well as in various civil engineering
applications. In spite of their better performance with different datasets,
support vector machines still suffer from shortcomings such as
visualization/interpretation of model, choice of kernel and kernel specific
parameter as well as the regularization parameter. Relevance vector machines
are another kernel based approach being explored for classification and
regression with in last few years. The advantages of the relevance vector
machines over the support vector machines is the availability of probabilistic
predictions, using arbitrary kernel functions and not requiring setting of the
regularization parameter. This paper presents a state-of-the-art review of SVM
and RVM in remote sensing and provides some details of their use in other civil
engineering application also.
|
1101.3051
|
Adaptive Variable Degree-k Zero-Trees for Re-Encoding of Perceptually
Quantized Wavelet-Packet Transformed Audio and High Quality Speech
|
cs.IT math.IT
|
A fast, efficient and scalable algorithm is proposed, in this paper, for
re-encoding of perceptually quantized wavelet-packet transform (WPT)
coefficients of audio and high quality speech and is called "adaptive variable
degree-k zero-trees" (AVDZ). The quantization process is carried out by taking
into account some basic perceptual considerations, and achieves good subjective
quality with low complexity. The performance of the proposed AVDZ algorithm is
compared with two other zero-tree-based schemes comprising: 1- Embedded
Zero-tree Wavelet (EZW) and 2- The set partitioning in hierarchical trees
(SPIHT). Since EZW and SPIHT are designed for image compression, some
modifications are incorporated in these schemes for their better matching to
audio signals. It is shown that the proposed modifications can improve their
performance by about 15-25%. Furthermore, it is concluded that the proposed
AVDZ algorithm outperforms these modified versions in terms of both output
average bit-rates and computation times.
|
1101.3068
|
Degrees of Freedom Region for an Interference Network with General
Message Demands
|
cs.IT math.IT
|
We consider a single hop interference network with $K$ transmitters and $J$
receivers, all having $M$ antennas. Each transmitter emits an independent
message and each receiver requests an arbitrary subset of the messages. This
generalizes the well-known $K$-user $M$-antenna interference channel, where
each message is requested by a unique receiver. For our setup, we derive the
degrees of freedom (DoF) region. The achievability scheme generalizes the
interference alignment schemes proposed by Cadambe and Jafar. In particular, we
achieve general points in the DoF region by using multiple base vectors and
aligning all interferers at a given receiver to the interferer with the largest
DoF. As a byproduct, we obtain the DoF region for the original interference
channel. We also discuss extensions of our approach where the same region can
be achieved by considering a reduced set of interference alignment constraints,
thus reducing the time-expansion duration needed. The DoF region for the
considered system depends only on a subset of receivers whose demands meet
certain characteristics. The geometric shape of the DoF region is also
discussed.
|
1101.3070
|
Information and the arrow of time
|
physics.pop-ph cs.IT math.IT
|
This paper is a discussion about the relationship between time and
information. We argue that the direction of arrow of time is related to the
directivity of information copying that occurs in Nature.
|
1101.3085
|
Simulating Opinion Dynamics in Heterogeneous Communication
|
cs.SI cs.MA physics.soc-ph
|
Since the information available is fundamental for our perceptions and
opinions, we are interested in understanding the conditions allowing for a good
information to be disseminated. This paper explores opinion dynamics by means
of multi-agent based simulations when agents get informed by different sources
of information. The scenario implemented includes three main streams of
information acquisition, differing in both the contents and the perceived
reliability of the messages spread. Agents' internal opinion is updated either
by accessing one of the information sources, namely media and experts, or by
exchanging information with one another. They are also endowed with cognitive
mechanisms to accept, reject or partially consider the acquired information. We
expect that peer-to--peer communication and reliable information sources are
able both to reduce biased perceptions and to inhibit information cheating,
possibly performed by the media as stated by the agenda-setting theory. In the
paper, after having shortly presented both the hypotheses and the model, the
simulation design will be specified and results will be discussed with respect
to the hypotheses. Some considerations and ideas for future studies will
conclude the paper.
|
1101.3098
|
Quantum Convex Support
|
math-ph cs.IT math.IT math.MP quant-ph
|
Convex support, the mean values of a set of random variables, is central in
information theory and statistics. Equally central in quantum information
theory are mean values of a set of observables in a finite-dimensional
C*-algebra A, which we call (quantum) convex support. The convex support can be
viewed as a projection of the state space of A and it is a projection of a
spectrahedron.
Spectrahedra are increasingly investigated at least since the 1990's boom in
semidefinite programming. We recall the geometry of the positive semi-definite
cone and of the state space. We write a convex duality for general self-dual
convex cones. This restricts to projections of state spaces and connects them
to results on spectrahedra.
Really new in this article is an analysis of the face lattice of convex
support by mapping this lattice to a lattice of orthogonal projections, using
natural isomorphisms. The result encodes the face lattice of the convex support
into a set of projections in A and enables the integration of convex geometry
with matrix calculus or algebraic techniques.
|
1101.3122
|
Digital herders and phase transition in a voting model
|
physics.soc-ph cond-mat.stat-mech cs.SI
|
In this paper, we discuss a voting model with two candidates, C_1 and C_2. We
set two types of voters--herders and independents. The voting of independent
voters is based on their fundamental values; on the other hand, the voting of
herders is based on the number of votes. Herders always select the majority of
the previous $r$ votes, which is visible to them. We call them digital herders.
We can accurately calculate the distribution of votes for special cases. When
r>=3, we find that a phase transition occurs at the upper limit of t, where t
is the discrete time (or number of votes). As the fraction of herders
increases, the model features a phase transition beyond which a state where
most voters make the correct choice coexists with one where most of them are
wrong. On the other hand, when r<3, there is no phase transition. In this case,
the herders' performance is the same as that of the independent voters.
Finally, we recognize the behavior of human beings by conducting simple
experiments.
|
1101.3124
|
SafeVchat: Detecting Obscene Content and Misbehaving Users in Online
Video Chat Services
|
cs.CR cs.CV cs.HC
|
Online video chat services such as Chatroulette, Omegle, and vChatter that
randomly match pairs of users in video chat sessions are fast becoming very
popular, with over a million users per month in the case of Chatroulette. A key
problem encountered in such systems is the presence of flashers and obscene
content. This problem is especially acute given the presence of underage minors
in such systems. This paper presents SafeVchat, a novel solution to the problem
of flasher detection that employs an array of image detection algorithms. A key
contribution of the paper concerns how the results of the individual detectors
are fused together into an overall decision classifying the user as misbehaving
or not, based on Dempster-Shafer Theory. The paper introduces a novel,
motion-based skin detection method that achieves significantly higher recall
and better precision. The proposed methods have been evaluated over real world
data and image traces obtained from Chatroulette.com.
|
1101.3149
|
Competition between Intra-community and Inter-community Synchronization
|
physics.soc-ph cs.SI nlin.AO
|
In this paper the effects of external links on the synchronization
performance of community networks, especially on the competition between
individual community and the whole network, are studied in detail. The study is
organized from two aspects: the number or portion of external links and the
connecting strategy of external links between different communities. It is
found that increasing the number of external links will enhance the global
synchronizability but degrade the ynchronization performance of individual
community before some critical point. After that the individual community will
synchronize better and better as part of the whole network because the
community structure is not so prominent. Among various connection strategies,
connecting nodes belonging to different communities randomly rather than
connecting nodes with larger degrees is the most efficient way to enhance
global synchronization of the network. However, a preferential connection
scheme linking most of the hubs from the communities will allow rather
efficient global synchronization while maintaining strong dynamical clustering
of the communities. Interestingly, the observations are found to be relevant in
a realistic network of cat cortex. The synchronization state is just at the
critical point, which shows a reasonable combination of segregated function in
individual communities and coordination among them. Our work sheds light on
principles underlying the emergence of modular architectures in real network
systems and provides guidance for the manipulation of synchronization in
community networks.
|
1101.3198
|
Towards Optimal Schemes for the Half-Duplex Two-Way Relay Channel
|
cs.IT math.IT
|
A restricted two-way communication problem in a small fully-connected network
is investigated. The network consists of three nodes, all having access to a
common channel with half-duplex constraint. Two nodes want to establish a
dialog while the third node can assist in the bi-directional transmission
process. All nodes have agreed on a transmission protocol a priori and the
problem is restricted to the dialog encoders not being allowed to establish a
cooperation by the use of previous receive signals. The channel is referred to
as the restricted half-duplex two-way relay channel. Here the channel is
defined and an outer bound on the achievable rates is derived by the
application of the cut-set theorem. This shows that the problem consists of six
parts. We propose a transmission protocol which takes into account all possible
transmit-receive configurations of the network and performs partial decoding of
the messages at the relay as well as sequential decoding at the dialog nodes.
By the use of random codes and suboptimal decoders, two inner bound on the
achievable rates are derived. Restricting to the suggested strategies and fixed
input distributions it is argued to be possible to determine optimal
transmission schemes with respect to various reasonable objectives at low
complexity. In comparison to two-way communication without relay, simulations
for an AWGN channel model then show that it is possible to simultaneously
increase the communication rates of both dialog messages and to outperform
relaying strategies that ignore an available direct path.
|
1101.3214
|
Generalized Belief Propagation for the Noiseless Capacity and
Information Rates of Run-Length Limited Constraints
|
cs.IT math.IT stat.CO
|
The performance of the generalized belief propagation algorithm for computing
the noiseless capacity and mutual information rates of finite-size
two-dimensional and three-dimensional run-length limited constraints is
investigated. For each constraint, a method is proposed to choose the basic
regions and to construct the region graph. Simulation results for the capacity
of different constraints as a function of the size of the channel and mutual
information rates of different constraints as a function of signal-to-noise
ratio are reported. Convergence to the Shannon capacity is also discussed.
|
1101.3220
|
Decision-Feedback Differential Detection in Impulse-Radio Ultra-Wideband
Systems
|
cs.IT math.IT
|
In this paper we present decision-feedback differential detection (DF-DD)
schemes for autocorrelation-based detection in impulse-radio ultra-wideband
(IR-UWB) systems, a signaling scheme regarded as a promising candidate in
particular for low-complexity wireless sensor networks. To this end, we first
discuss ideal noncoherent sequence estimation and approximations thereof based
on block-wise multiple-symbol differential detection (MSDD) and the Viterbi
algorithm (VA) from the perspective of tree-search/trellis decoding. Exploiting
relations well-known from tree-search decoding, we are able to derive the novel
decision-feedback differential detection (DF-DD) schemes. A comprehensive
comparison with respect to performance and complexity of the presented schemes
in a typical IR-UWB scenario reveals---along with novel insights in techniques
for complexity reduction of the sphere decoder applied for MSDD---that sorted
DF-DD achieves close-to-optimum performance at very low, and in particular
constant receiver complexity.
|
1101.3285
|
A note on the multiple unicast capacity of directed acyclic networks
|
cs.IT math.IT
|
We consider the multiple unicast problem under network coding over directed
acyclic networks with unit capacity edges. There is a set of n source-terminal
(s_i - t_i) pairs that wish to communicate at unit rate over this network. The
connectivity between the s_i - t_i pairs is quantified by means of a
connectivity level vector, [k_1 k_2 ... k_n] such that there exist k_i
edge-disjoint paths between s_i and t_i. Our main aim is to characterize the
feasibility of achieving this for different values of n and [k_1 ... k_n]. For
3 unicast connections (n = 3), we characterize several achievable and
unachievable values of the connectivity 3-tuple. In addition, in this work, we
have found certain network topologies, and capacity characterizations that are
useful in understanding the case of general n.
|
1101.3291
|
Node Classification in Social Networks
|
cs.SI physics.soc-ph
|
When dealing with large graphs, such as those that arise in the context of
online social networks, a subset of nodes may be labeled. These labels can
indicate demographic values, interest, beliefs or other characteristics of the
nodes (users). A core problem is to use this information to extend the labeling
so that all nodes are assigned a label (or labels). In this chapter, we survey
classification techniques that have been proposed for this problem. We consider
two broad categories: methods based on iterative application of traditional
classifiers using graph information as features, and methods which propagate
the existing labels via random walks. We adopt a common perspective on these
methods to highlight the similarities between different approaches within and
across the two categories. We also describe some extensions and related
directions to the central problem of node classification.
|
1101.3341
|
Collaborative Filtering without Explicit Feedbacks for Digital Recorders
|
cs.IR cs.HC
|
Recommendation is usually reduced to a prediction problem over the function
$r(u_a, e_i)$ that returns the expected rating of element $e_i$ for user $u_a$.
In the IPTV domain, we deal with an environment where the definitions of all
the parameters involved in this function (i.e., user profiles, feedback ratings
and elements) are controversial. To our knowledge, this paper represents the
first attempt to run collaborative filtering algorithms without inner
assumptions: we start our analysis from an unstructured set of recordings,
before performing a data pre-processing phase in order to extract useful
information. Hence, we experiment with a real Digital Video Recorder system
where EPG have not been provided to the user for selecting event timings and
where explicit feedbacks were not collected.
|
1101.3348
|
Structured sublinear compressive sensing via belief propagation
|
cs.IT math.IT
|
Compressive sensing (CS) is a sampling technique designed for reducing the
complexity of sparse data acquisition. One of the major obstacles for practical
deployment of CS techniques is the signal reconstruction time and the high
storage cost of random sensing matrices. We propose a new structured
compressive sensing scheme, based on codes of graphs, that allows for a joint
design of structured sensing matrices and logarithmic-complexity reconstruction
algorithms. The compressive sensing matrices can be shown to offer
asymptotically optimal performance when used in combination with Orthogonal
Matching Pursuit (OMP) methods. For more elaborate greedy reconstruction
schemes, we propose a new family of list decoding belief propagation
algorithms, as well as reinforced- and multiple-basis belief propagation
algorithms. Our simulation results indicate that reinforced BP CS schemes offer
very good complexity-performance tradeoffs for very sparse signal vectors.
|
1101.3352
|
Dimensional behaviour of entropy and information
|
math.FA cs.IT math.IT math.PR
|
We develop an information-theoretic perspective on some questions in convex
geometry, providing for instance a new equipartition property for log-concave
probability measures, some Gaussian comparison results for log-concave
measures, an entropic formulation of the hyperplane conjecture, and a new
reverse entropy power inequality for log-concave measures analogous to V.
Milman's reverse Brunn-Minkowski inequality.
|
1101.3354
|
Introduction to the Bag of Features Paradigm for Image Classification
and Retrieval
|
cs.CV cs.IR
|
The past decade has seen the growing popularity of Bag of Features (BoF)
approaches to many computer vision tasks, including image classification, video
search, robot localization, and texture recognition. Part of the appeal is
simplicity. BoF methods are based on orderless collections of quantized local
image descriptors; they discard spatial information and are therefore
conceptually and computationally simpler than many alternative methods. Despite
this, or perhaps because of this, BoF-based systems have set new performance
standards on popular image classification benchmarks and have achieved
scalability breakthroughs in image retrieval. This paper presents an
introduction to BoF image representations, describes critical design choices,
and surveys the BoF literature. Emphasis is placed on recent techniques that
mitigate quantization errors, improve feature detection, and speed up image
retrieval. At the same time, unresolved issues and fundamental challenges are
raised. Among the unresolved issues are determining the best techniques for
sampling images, describing local image features, and evaluating system
performance. Among the more fundamental challenges are how and whether BoF
methods can contribute to localizing objects in complex images, or to
associating high-level semantics with natural images. This survey should be
useful both for introducing new investigators to the field and for providing
existing researchers with a consolidated reference to related work.
|
1101.3381
|
Efficient Independence-Based MAP Approach for Robust Markov Networks
Structure Discovery
|
cs.AI cs.CV
|
This work introduces the IB-score, a family of independence-based score
functions for robust learning of Markov networks independence structures.
Markov networks are a widely used graphical representation of probability
distributions, with many applications in several fields of science. The main
advantage of the IB-score is the possibility of computing it without the need
of estimation of the numerical parameters, an NP-hard problem, usually solved
through an approximate, data-intensive, iterative optimization. We derive a
formal expression for the IB-score from first principles, mainly maximum a
posteriori and conditional independence properties, and exemplify several
instantiations of it, resulting in two novel algorithms for structure learning:
IBMAP-HC and IBMAP-TS. Experimental results over both artificial and real world
data show these algorithms achieve important error reductions in the learnt
structures when compared with the state-of-the-art independence-based structure
learning algorithm GSMN, achieving increments of more than 50% in the amount of
independencies they encode correctly, and in some cases, learning correctly
over 90% of the edges that GSMN learnt incorrectly. Theoretical analysis shows
IBMAP-HC proceeds efficiently, achieving these improvements in a time
polynomial to the number of random variables in the domain.
|
1101.3391
|
Automated Image Processing for the Analysis of DNA Repair Dynamics
|
cs.CV q-bio.QM
|
The efficient repair of cellular DNA is essential for the maintenance and
inheritance of genomic information. In order to cope with the high frequency of
spontaneous and induced DNA damage, a multitude of repair mechanisms have
evolved. These are enabled by a wide range of protein factors specifically
recognizing different types of lesions and finally restoring the normal DNA
sequence. This work focuses on the repair factor XPC (xeroderma pigmentosum
complementation group C), which identifies bulky DNA lesions and initiates
their removal via the nucleotide excision repair pathway. The binding of XPC to
damaged DNA can be visualized in living cells by following the accumulation of
a fluorescent XPC fusion at lesions induced by laser microirradiation in a
fluorescence microscope. In this work, an automated image processing pipeline
is presented which allows to identify and quantify the accumulation reaction
without any user interaction. The image processing pipeline comprises a
preprocessing stage where the image stack data is filtered and the nucleus of
interest is segmented. Afterwards, the images are registered to each other in
order to account for movements of the cell, and then a bounding box enclosing
the XPC-specific signal is automatically determined. Finally, the
time-dependent relocation of XPC is evaluated by analyzing the intensity change
within this box. Comparison of the automated processing results with the manual
evaluation yields qualitatively similar results. However, the automated
analysis provides more accurate, reproducible data with smaller standard
errors. The image processing pipeline presented in this work allows for an
efficient analysis of large amounts of experimental data with no user
interaction required.
|
1101.3393
|
Traffic properties for stochastic routings on scale-free networks
|
physics.soc-ph cond-mat.stat-mech cs.SI
|
For realistic scale-free networks, we investigate the traffic properties of
stochastic routing inspired by a zero-range process known in statistical
physics. By parameters $\alpha$ and $\delta$, this model controls
degree-dependent hopping of packets and forwarding of packets with higher
performance at more busy nodes. Through a theoretical analysis and numerical
simulations, we derive the condition for the concentration of packets at a few
hubs. In particular, we show that the optimal $\alpha$ and $\delta$ are
involved in the trade-off between a detour path for $\alpha < 0$ and long wait
at hubs for $\alpha > 0$; In the low-performance regime at a small $\delta$,
the wandering path for $\alpha < 0$ better reduces the mean travel time of a
packet with high reachability. Although, in the high-performance regime at a
large $\delta$, the difference between $\alpha > 0$ and $\alpha < 0$ is small,
neither the wandering long path with short wait trapped at nodes ($\alpha =
-1$), nor the short hopping path with long wait trapped at hubs ($\alpha = 1$)
is advisable. A uniformly random walk ($\alpha = 0$) yields slightly better
performance. We also discuss the congestion phenomena in a more complicated
situation with packet generation at each time step.
|
1101.3398
|
New Quadriphase Sequences families with Larger Linear Span and Size
|
cs.IT math.IT
|
In this paper, new families of quadriphase sequences with larger linear span
and size have been proposed and studied. In particular, a new family of
quadriphase sequences of period $2^n-1$ for a positive integer $n=em$ with an
even positive factor $m$ is presented, the cross-correlation function among
these sequences has been explicitly calculated. Another new family of
quadriphase sequences of period $2(2^n-1)$ for a positive integer $n=em$ with
an even positive factor $m$ is also presented, a detailed analysis of the
cross-correlation function of proposed sequences has also been presented.
|
1101.3400
|
Behavioral On-Line Advertising
|
cs.IR
|
We present a new algorithm for behavioral targeting of banner advertisements.
We record different user's actions such as clicks, search queries and page
views. We use the collected information on the user to estimate in real time
the probability of a click on a banner. A banner is displayed if it either has
the highest probability of being clicked or if it is the one that generates the
highest average profit.
|
1101.3444
|
Control of Wireless Networks with Secrecy
|
cs.IT cs.DC math.IT
|
We consider the problem of cross-layer resource allocation in time-varying
cellular wireless networks, and incorporate information theoretic secrecy as a
Quality of Service constraint. Specifically, each node in the network injects
two types of traffic, private and open, at rates chosen in order to maximize a
global utility function, subject to network stability and secrecy constraints.
The secrecy constraint enforces an arbitrarily low mutual information leakage
from the source to every node in the network, except for the sink node. We
first obtain the achievable rate region for the problem for single and
multi-user systems assuming that the nodes have full CSI of their neighbors.
Then, we provide a joint flow control, scheduling and private encoding scheme,
which does not rely on the knowledge of the prior distribution of the gain of
any channel. We prove that our scheme achieves a utility, arbitrarily close to
the maximum achievable utility. Numerical experiments are performed to verify
the analytical results, and to show the efficacy of the dynamic control
algorithm.
|
1101.3453
|
Algebraic Foundations for Information Theoretical, Probabilistic and
Guessability measures of Information Flow
|
cs.IT math.IT
|
Several mathematical ideas have been investigated for Quantitative
Information Flow. Information theory, probability, guessability are the main
ideas in most proposals. They aim to quantify how much information is leaked,
how likely is to guess the secret and how long does it take to guess the secret
respectively. In this paper, we show how the Lattice of Information provides a
valuable foundation for all these approaches; not only it provides an elegant
algebraic framework for the ideas, but also to investigate their relationship.
In particular we will use this lattice to prove some results establishing order
relation correspondences between the different quantitative approaches. The
implications of these results w.r.t. recent work in the community is also
investigated. While this work concentrates on the foundational importance of
the Lattice of Information its practical relevance has been recently proven,
notably with the quantitative analysis of Linux kernel vulnerabilities. Overall
we believe these works set the case for establishing the Lattice of Information
as one of the main reference structure for Quantitative Information Flow.
|
1101.3457
|
Capacity of DNA Data Embedding Under Substitution Mutations
|
cs.IT math.IT q-bio.PE q-bio.QM
|
A number of methods have been proposed over the last decade for encoding
information using deoxyribonucleic acid (DNA), giving rise to the emerging area
of DNA data embedding. Since a DNA sequence is conceptually equivalent to a
sequence of quaternary symbols (bases), DNA data embedding (diversely called
DNA watermarking or DNA steganography) can be seen as a digital communications
problem where channel errors are tantamount to mutations of DNA bases.
Depending on the use of coding or noncoding DNA hosts, which, respectively,
denote DNA segments that can or cannot be translated into proteins, DNA data
embedding is essentially a problem of communications with or without side
information at the encoder. In this paper the Shannon capacity of DNA data
embedding is obtained for the case in which DNA sequences are subject to
substitution mutations modelled using the Kimura model from molecular evolution
studies. Inferences are also drawn with respect to the biological implications
of some of the results presented.
|
1101.3465
|
The "psychological map of the brain", as a personal information card
(file), - a project for the student of the 21st century
|
cs.AI
|
We suggest a procedure that is relevant both to electronic performance and
human psychology, so that the creative logic and the respect for human nature
appear in a good agreement. The idea is to create an electronic card containing
basic information about a person's psychological behavior in order to make it
possible to quickly decide about the suitability of one for another. This
"psychological electronics" approach could be tested via student projects.
|
1101.3500
|
Computation for Supremal Simulation-Based Controllable and Strong
Observable Subautomata
|
cs.SY
|
Bisimulation relation has been successfully applied to computer science and
control theory. In our previous work, simulation-based controllability and
simulation-based observability are proposed, under which the existence of
bisimilarity supervisor is guaranteed. However, a given specification automaton
may not satisfy these conditions, and a natural question is how to compute a
maximum permissive subspecification. This paper aims to answer this question
and investigate the computation of the supremal simulation-based controllable
and strong observable subautomata with respect to given specifications by the
lattice theory. In order to achieve the supremal solution, three monotone
operators, namely simulation operator, controllable operator and strong
observable operator, are proposed upon the established complete lattice. Then,
inequalities based on these operators are formulated, whose solution is the
simulation-based controllable and strong observable set. In particular, a
sufficient condition is presented to guarantee the existence of the supremal
simulation-based controllable and strong observable subautomata. Furthermore,
an algorithm is proposed to compute such subautomata.
|
1101.3574
|
A Game-Theoretic View of the Interference Channel: Impact of
Coordination and Bargaining
|
cs.IT math.IT
|
This work considers coordination and bargaining between two selfish users
over a Gaussian interference channel. The usual information theoretic approach
assumes full cooperation among users for codebook and rate selection. In the
scenario investigated here, each user is willing to coordinate its actions only
when an incentive exists and benefits of cooperation are fairly allocated. The
users are first allowed to negotiate for the use of a simple Han-Kobayashi type
scheme with fixed power split. Conditions for which users have incentives to
cooperate are identified. Then, two different approaches are used to solve the
associated bargaining problem. First, the Nash Bargaining Solution (NBS) is
used as a tool to get fair information rates and the operating point is
obtained as a result of an optimization problem. Next, a dynamic
alternating-offer bargaining game (AOBG) from bargaining theory is introduced
to model the bargaining process and the rates resulting from negotiation are
characterized. The relationship between the NBS and the equilibrium outcome of
the AOBG is studied and factors that may affect the bargaining outcome are
discussed. Finally, under certain high signal-to-noise ratio regimes, the
bargaining problem for the generalized degrees of freedom is studied.
|
1101.3578
|
Infinity in computable probability
|
math.LO cs.CL cs.LO
|
Does combining a finite collection of objects infinitely many times guarantee
the construction of a particular object? Here we use recursive function theory
to examine the popular scenario of an infinite collection of typing monkeys
reproducing the works of Shakespeare. Our main result is to show that it is
possible to assign typing probabilities in such a way that while it is
impossible that no monkey reproduces Shakespeare's works, the probability of
any finite collection of monkeys doing so is arbitrarily small. We extend our
results to target-free writing, and end with a broad discussion and pointers to
future work.
|
1101.3594
|
Classification under Data Contamination with Application to Remote
Sensing Image Mis-registration
|
stat.ME cs.LG stat.ML
|
This work is motivated by the problem of image mis-registration in remote
sensing and we are interested in determining the resulting loss in the accuracy
of pattern classification. A statistical formulation is given where we propose
to use data contamination to model and understand the phenomenon of image
mis-registration. This model is widely applicable to many other types of errors
as well, for example, measurement errors and gross errors etc. The impact of
data contamination on classification is studied under a statistical learning
theoretical framework. A closed-form asymptotic bound is established for the
resulting loss in classification accuracy, which is less than
$\epsilon/(1-\epsilon)$ for data contamination of an amount of $\epsilon$. Our
bound is sharper than similar bounds in the domain adaptation literature and,
unlike such bounds, it applies to classifiers with an infinite
Vapnik-Chervonekis (VC) dimension. Extensive simulations have been conducted on
both synthetic and real datasets under various types of data contamination,
including label flipping, feature swapping and the replacement of feature
values with data generated from a random source such as a Gaussian or Cauchy
distribution. Our simulation results show that the bound we derive is fairly
tight.
|
1101.3620
|
Clustering Protein Sequences Given the Approximation Stability of the
Min-Sum Objective Function
|
cs.DS cs.CE
|
We study the problem of efficiently clustering protein sequences in a limited
information setting. We assume that we do not know the distances between the
sequences in advance, and must query them during the execution of the
algorithm. Our goal is to find an accurate clustering using few queries. We
model the problem as a point set $S$ with an unknown metric $d$ on $S$, and
assume that we have access to \emph{one versus all} distance queries that given
a point $s \in S$ return the distances between $s$ and all other points. Our
one versus all query represents an efficient sequence database search program
such as BLAST, which compares an input sequence to an entire data set. Given a
natural assumption about the approximation stability of the \emph{min-sum}
objective function for clustering, we design a provably accurate clustering
algorithm that uses few one versus all queries. In our empirical study we show
that our method compares favorably to well-established clustering algorithms
when we compare computationally derived clusterings to gold-standard manual
classifications.
|
1101.3684
|
Bio-inspired Methods for Dynamic Network Analysis in Science Mapping
|
cs.DL cs.SI physics.soc-ph
|
We apply bio-inspired methods for the analysis of different dynamic
bibliometric networks (linking papers by citation, authors, and keywords,
respectively). Biological species are clusters of individuals defined by widely
different criteria and in the biological perspective it is natural to (1) use
different categorizations on the same entities (2) to compare the different
categorizations and to analyze the dissimilarities, especially as they change
over time. We employ the same methodology to comparisons of bibliometric
classifications. We constructed them as analogs of three species concepts:
cladistic or lineage based, similarity based, and "biological species" (based
on co-reproductive ability). We use the Rand and Jaccard indexes to compare
classifications in different time intervals. The experiment is aimed to address
the classic problem of science mapping, as to what extent the various
techniques based on different bibliometric indicators, such as citations,
keywords or authors are able to detect convergent structures in the
litrerature, that is, to identify coherent specialities or research directions
and their dynamics.
|
1101.3719
|
Trip Length Distribution Under Multiplicative Spatial Models of Supply
and Demand: Theory and Sensitivity Analysis
|
physics.data-an cs.SI physics.soc-ph
|
We propose new probabilistic models for the spatial distribution of supply
and demand and use the models to determine how the trip length distribution is
affected by the relative shortage or excess of supply, the spatial clustering
of supply and demand, and the degree of attraction or repulsion between supply
and demand at different spatial scales. The models have a multiplicative
structure and in certain cases possess scale invariance properties. Using
detailed population data in metropolitan US regions validates the demand model.
The trip length distribution, evaluated under destination choice models of the
intervening opportunities type, has quasi-analytic form.We take advantage of
this feature to study the sensitivity of the trip length distribution to
parameters of the demand, supply and destination choice models. We find that
trip length is affected in important but different ways by the spatial density
of potential destinations, the dependence among their attractiveness levels,
and the correlation between supply and demand at different spatial scales.
|
1101.3724
|
Throughput-Delay Analysis of Random Linear Network Coding for Wireless
Broadcasting
|
cs.IT math.IT
|
In an unreliable single-hop broadcast network setting, we investigate the
throughput and decoding-delay performance of random linear network coding as a
function of the coding window size and the network size. Our model consists of
a source transmitting packets of a single flow to a set of $n$ users over
independent erasure channels. The source performs random linear network coding
(RLNC) over $k$ (coding window size) packets and broadcasts them to the users.
We note that the broadcast throughput of RLNC must vanish with increasing $n$,
for any fixed $k.$ Hence, in contrast to other works in the literature, we
investigate how the coding window size $k$ must scale for increasing $n$. Our
analysis reveals that the coding window size of $\Theta(\ln(n))$ represents a
phase transition rate, below which the throughput converges to zero, and above
which it converges to the broadcast capacity. Further, we characterize the
asymptotic distribution of decoding delay and provide approximate expressions
for the mean and variance of decoding delay for the scaling regime of
$k=\omega(\ln(n)).$ These asymptotic expressions reveal the impact of channel
correlations on the throughput and delay performance of RLNC. We also show how
our analysis can be extended to other rateless block coding schemes such as the
LT codes. Finally, we comment on the extension of our results to the cases of
dependent channels across users and asymmetric channel model.
|
1101.3735
|
Formalising the multidimensional nature of social networks
|
physics.soc-ph cs.SI q-bio.PE
|
Individuals interact with conspecifics in a number of behavioural contexts or
dimensions. Here, we formalise this by considering a social network between n
individuals interacting in b behavioural dimensions as a nxnxb multidimensional
object. In addition, we propose that the topology of this object is driven by
individual needs to reduce uncertainty about the outcomes of interactions in
one or more dimension. The proposal grounds social network dynamics and
evolution in individual selection processes and allows us to define the
uncertainty of the social network as the joint entropy of its constituent
interaction networks. In support of these propositions we use simulations and
natural 'knock-outs' in a free-ranging baboon troop to show (i) that such an
object can display a small-world state and (ii) that, as predicted, changes in
interactions after social perturbations lead to a more certain social network,
in which the outcomes of interactions are easier for members to predict. This
new formalisation of social networks provides a framework within which to
predict network dynamics and evolution under the assumption that it is driven
by individuals seeking to reduce the uncertainty of their social environment.
|
1101.3755
|
Transductive-Inductive Cluster Approximation Via Multivariate Chebyshev
Inequality
|
cs.CV cs.AI
|
Approximating adequate number of clusters in multidimensional data is an open
area of research, given a level of compromise made on the quality of acceptable
results. The manuscript addresses the issue by formulating a transductive
inductive learning algorithm which uses multivariate Chebyshev inequality.
Considering clustering problem in imaging, theoretical proofs for a particular
level of compromise are derived to show the convergence of the reconstruction
error to a finite value with increasing (a) number of unseen examples and (b)
the number of clusters, respectively. Upper bounds for these error rates are
also proved. Non-parametric estimates of these error from a random sample of
sequences empirically point to a stable number of clusters. Lastly, the
generalization of algorithm can be applied to multidimensional data sets from
different fields.
|
1101.3761
|
Tagging with DHARMA, a DHT-based Approach for Resource Mapping through
Approximation
|
cs.DC cs.SI
|
We introduce collaborative tagging and faceted search on structured P2P
systems. Since a trivial and brute force mapping of an entire folksonomy over a
DHT-based system may reduce scalability, we propose an approximated graph
maintenance approach. Evaluations on real data coming from Last.fm prove that
such strategies reduce vocabulary noise (i.e., representation's overfitting
phenomena) and hotspots issues.
|
1101.3774
|
Secret Key Agreement Over Multipath Channels Exploiting a
Variable-Directional Antenna
|
cs.IT math.IT
|
We develop an approach of key distribution protocol (KDP) proposed recently
by T. Aono et al. A more general mathematical model based on the use of
Variable-Directional Antenna (VDA) under the condition of multipath wave
propagation is proposed. Statistical characteristics of VDA were investigated
by simulation, that allows us to specify model parameters. The security of the
considered KDP is estimated in terms of Shannon's information leaking to an
eavesdropper depending on the mutual locations of the legal users and the
eavesdropper.
Antenna diversity is proposed as a mean to enhance the KDP security. In order
to provide a better agreement of the shared keys it is investigated the use of
error-correcting codes.
|
1101.3824
|
Series Expansion for Interference in Wireless Networks
|
cs.IT math.IT math.PR stat.AP
|
The spatial correlations in transmitter node locations introduced by common
multiple access protocols makes the analysis of interference, outage, and other
related metrics in a wireless network extremely difficult. Most works therefore
assume that nodes are distributed either as a Poisson point process (PPP) or a
grid, and utilize the independence properties of the PPP (or the regular
structure of the grid) to analyze interference, outage and other metrics.
But,the independence of node locations makes the PPP a dubious model for
nontrivial MACs which intentionally introduce correlations, e.g. spatial
separation, while the grid is too idealized to model real networks. In this
paper, we introduce a new technique based on the factorial moment expansion of
functionals of point processes to analyze functions of interference, in
particular outage probability. We provide a Taylor-series type expansion of
functions of interference, wherein increasing the number of terms in the series
provides a better approximation at the cost of increased complexity of
computation. Various examples illustrate how this new approach can be used to
find outage probability in both Poisson and non-Poisson wireless networks.
|
1101.3838
|
Performance Bounds for Sparse Parametric Covariance Estimation in
Gaussian Models
|
cs.IT math.IT math.ST stat.TH
|
We consider estimation of a sparse parameter vector that determines the
covariance matrix of a Gaussian random vector via a sparse expansion into known
"basis matrices". Using the theory of reproducing kernel Hilbert spaces, we
derive lower bounds on the variance of estimators with a given mean function.
This includes unbiased estimation as a special case. We also present a
numerical comparison of our lower bounds with the variance of two standard
estimators (hard-thresholding estimator and maximum likelihood estimator).
|
1101.3885
|
An Upper Bound for Signal Transmission Error Probability in Hyperbolic
Spaces
|
cs.IT math.IT
|
We introduce and discuss the concept of Gaussian probability density function
(pdf) for the n-dimensional hyperbolic space which has been proposed as an
environment for coding and decoding signals. An upper bound for the error
probability of signal transmission associated with the hyperbolic distance is
established. The pdf and the upper bound were developed using Poincare models
for the hyperbolic spaces.
|
1101.3929
|
Characteristic Generators and Dualization for Tail-Biting Trellises
|
cs.IT math.IT
|
This paper focuses on dualizing tail-biting trellises, particularly
KV-trellises. These trellises are based on characteristic generators, as
introduced by Koetter/Vardy (2003), and may be regarded as a natural
generalization of minimal conventional trellises, even though they are not
necessarily minimal. Two dualization techniques will be investigated: the local
dualization, introduced by Forney (2001) for general normal graphs, and a
linear algebra based dualization tailored to the specific class of tail-biting
BCJR-trellises, introduced by Nori/Shankar (2006). It turns out that, in
general, the BCJR-dual is a subtrellis of the local dual, while for
KV-trellises these two coincide. Furthermore, making use of both the
BCJR-construction and the local dualization, it will be shown that for each
complete set of characteristic generators of a code there exists a complete set
of characteristic generators of the dual code such that their resulting
KV-trellises are dual to each other if paired suitably. This proves a stronger
version of a conjecture formulated by Koetter/Vardy.
|
1101.3973
|
On cooperative patrolling: optimal trajectories, complexity analysis,
and approximation algorithms
|
math.CO cs.DS cs.SY math.OC
|
The subject of this work is the patrolling of an environment with the aid of
a team of autonomous agents. We consider both the design of open-loop
trajectories with optimal properties, and of distributed control laws
converging to optimal trajectories. As performance criteria, the refresh time
and the latency are considered, i.e., respectively, time gap between any two
visits of the same region, and the time necessary to inform every agent about
an event occurred in the environment. We associate a graph with the
environment, and we study separately the case of a chain, tree, and cyclic
graph. For the case of chain graph, we first describe a minimum refresh time
and latency team trajectory, and we propose a polynomial time algorithm for its
computation. Then, we describe a distributed procedure that steers the robots
toward an optimal trajectory. For the case of tree graph, a polynomial time
algorithm is developed for the minimum refresh time problem, under the
technical assumption of a constant number of robots involved in the patrolling
task. Finally, we show that the design of a minimum refresh time trajectory for
a cyclic graph is NP-hard, and we develop a constant factor approximation
algorithm.
|
1101.3979
|
Selection of network coding nodes for minimal playback delay in
streaming overlays
|
cs.MM cs.IT cs.NI math.IT
|
Network coding permits to deploy distributed packet delivery algorithms that
locally adapt to the network availability in media streaming applications.
However, it may also increase delay and computational complexity if it is not
implemented efficiently. We address here the effective placement of nodes that
implement randomized network coding in overlay networks, so that the goodput is
kept high while the delay for decoding stays small in streaming applications.
We first estimate the decoding delay at each client, which depends on the
innovative rate in the network. This estimation permits to identify the nodes
that have to perform coding for a reduced decoding delay. We then propose two
iterative algorithms for selecting the nodes that should perform network
coding. The first algorithm relies on the knowledge of the full network
statistics. The second algorithm uses only local network statistics at each
node. Simulation results show that large performance gains can be achieved with
the selection of only a few network coding nodes. Moreover, the second
algorithm performs very closely to the central estimation strategy, which
demonstrates that the network coding nodes can be selected efficiently in a
distributed manner. Our scheme shows large gains in terms of achieved
throughput, delay and video quality in realistic overlay networks when compared
to methods that employ traditional streaming strategies as well as random
network nodes selection algorithms.
|
1101.4003
|
Dyna-H: a heuristic planning reinforcement learning algorithm applied to
role-playing-game strategy decision systems
|
cs.AI cs.LG cs.SY math.OC
|
In a Role-Playing Game, finding optimal trajectories is one of the most
important tasks. In fact, the strategy decision system becomes a key component
of a game engine. Determining the way in which decisions are taken (online,
batch or simulated) and the consumed resources in decision making (e.g.
execution time, memory) will influence, in mayor degree, the game performance.
When classical search algorithms such as A* can be used, they are the very
first option. Nevertheless, such methods rely on precise and complete models of
the search space, and there are many interesting scenarios where their
application is not possible. Then, model free methods for sequential decision
making under uncertainty are the best choice. In this paper, we propose a
heuristic planning strategy to incorporate the ability of heuristic-search in
path-finding into a Dyna agent. The proposed Dyna-H algorithm, as A* does,
selects branches more likely to produce outcomes than other branches. Besides,
it has the advantages of being a model-free online reinforcement learning
algorithm. The proposal was evaluated against the one-step Q-Learning and
Dyna-Q algorithms obtaining excellent experimental results: Dyna-H
significantly overcomes both methods in all experiments. We suggest also, a
functional analogy between the proposed sampling from worst trajectories
heuristic and the role of dreams (e.g. nightmares) in human behavior.
|
1101.4028
|
Who is the best player ever? A complex network analysis of the history
of professional tennis
|
physics.soc-ph cs.SI physics.pop-ph
|
We consider all matches played by professional tennis players between 1968
and 2010, and, on the basis of this data set, construct a directed and weighted
network of contacts. The resulting graph shows complex features, typical of
many real networked systems studied in literature. We develop a diffusion
algorithm and apply it to the tennis contact network in order to rank
professional players. Jimmy Connors is identified as the best player of the
history of tennis according to our ranking procedure. We perform a complete
analysis by determining the best players on specific playing surfaces as well
as the best ones in each of the years covered by the data set. The results of
our technique are compared to those of two other well established methods. In
general, we observe that our ranking method performs better: it has a higher
predictive power and does not require the arbitrary introduction of external
criteria for the correct assessment of the quality of players. The present work
provides a novel evidence of the utility of tools and methods of network theory
in real applications.
|
1101.4036
|
Secure Multiplex Coding with a Common Message
|
cs.IT cs.CR math.IT
|
We determine the capacity region of the secure multiplex coding with a common
message, and evaluate the mutual information and the equivocation rate of a
collection of secret messages to the second receiver (eavesdropper), which were
not evaluated by Yamamoto et al.
|
1101.4075
|
PMI-based MIMO OFDM PHY Integrated Key Exchange (P-MOPI) Scheme
|
cs.IT math.IT
|
In the literature, J.-P. Cheng et al. have proposed the MIMO-OFDM PHY
integrated (MOPI) scheme for achieving physical-layer security in practice
without using any cryptographic ciphers. The MOPI scheme uses channel sounding
and physical-layer network coding (PNC) to prevent eavesdroppers from learning
the channel state information (CSI). Nevertheless, due to the use of multiple
antennas for PNC at transmitter and beamforming at receiver, it is not possible
to have spatial multiplexing nor use space-time codes in our previous MOPI
scheme. In this paper, we propose a variant of the MOPI scheme, called P-MOPI,
that works with a cryptographic cipher and utilizes precoding matrix index
(PMI) as an efficient key-exchange mechanism. With channel sounding, the PMI is
only known between the transmitter and the legal receiver. The shared key can
then be used, e.g., as the seed to generate pseudo random bit sequences for
securing subsequent transmissions using a stream cipher. By applying the same
techniques at independent subcarriers of the OFDM system, the P-MOPI scheme
easily allows two communicating parties to exchange over 100 secret bits. As a
result, not only secure communication but also the MIMO gain can be guaranteed
by using the P-MOPI scheme.
|
1101.4100
|
Reconciling Compressive Sampling Systems for Spectrally-sparse
Continuous-time Signals
|
cs.IT math.IT
|
The Random Demodulator (RD) and the Modulated Wideband Converter (MWC) are
two recently proposed compressed sensing (CS) techniques for the acquisition of
continuous-time spectrally-sparse signals. They extend the standard CS paradigm
from sampling discrete, finite dimensional signals to sampling continuous and
possibly infinite dimensional ones, and thus establish the ability to capture
these signals at sub-Nyquist sampling rates. The RD and the MWC have remarkably
similar structures (similar block diagrams), but their reconstruction
algorithms and signal models strongly differ. To date, few results exist that
compare these systems, and owing to the potential impacts they could have on
spectral estimation in applications like electromagnetic scanning and cognitive
radio, we more fully investigate their relationship in this paper. We show that
the RD and the MWC are both based on the general concept of random filtering,
but employ significantly different sampling functions. We also investigate
system sensitivities (or robustness) to sparse signal model assumptions.
Lastly, we show that "block convolution" is a fundamental aspect of the MWC,
allowing it to successfully sample and reconstruct block-sparse (multiband)
signals. Based on this concept, we propose a new acquisition system for
continuous-time signals whose amplitudes are block sparse. The paper includes
detailed time and frequency domain analyses of the RD and the MWC that differ,
sometimes substantially, from published results.
|
1101.4101
|
Context Capture in Software Development
|
cs.SE cs.AI
|
The context of a software developer is something hard to define and capture,
as it represents a complex network of elements across different dimensions that
are not limited to the work developed on an IDE. We propose the definition of a
software developer context model that takes into account all the dimensions
that characterize the work environment of the developer. We are especially
focused on what the software developer context encompasses at the project level
and how it can be captured. The experimental work done so far show that useful
context information can be extracted from project management tools. The
extraction, analysis and availability of this context information can be used
to enrich the work environment of the developer with additional knowledge to
support her/his work.
|
1101.4103
|
Evolutionary Mechanics: new engineering principles for the emergence of
flexibility in a dynamic and uncertain world
|
nlin.AO cs.AI
|
Engineered systems are designed to deftly operate under predetermined
conditions yet are notoriously fragile when unexpected perturbations arise. In
contrast, biological systems operate in a highly flexible manner; learn quickly
adequate responses to novel conditions, and evolve new routines/traits to
remain competitive under persistent environmental change. A recent theory on
the origins of biological flexibility has proposed that degeneracy - the
existence of multi-functional components with partially overlapping functions -
is a primary determinant of the robustness and adaptability found in evolved
systems. While degeneracy's contribution to biological flexibility is well
documented, there has been little investigation of degeneracy design principles
for achieving flexibility in systems engineering. Actually, the conditions that
can lead to degeneracy are routinely eliminated in engineering design.
With the planning of transportation vehicle fleets taken as a case study,
this paper reports evidence that degeneracy improves robustness and
adaptability of a simulated fleet without incurring costs to efficiency. We
find degeneracy dramatically increases robustness of a fleet to unpredicted
changes in the environment while it also facilitates robustness to anticipated
variations. When we allow a fleet's architecture to be adapted in response to
environmental change, we find degeneracy can be selectively acquired, leading
to faster rates of design adaptation and ultimately to better designs. Given
the range of conditions where favorable short-term and long-term performance
outcomes are observed, we propose that degeneracy design principles
fundamentally alter the propensity for adaptation and may be useful within
several engineering and planning contexts.
|
1101.4170
|
The Role of Normalization in the Belief Propagation Algorithm
|
cs.LG
|
An important part of problems in statistical physics and computer science can
be expressed as the computation of marginal probabilities over a Markov Random
Field. The belief propagation algorithm, which is an exact procedure to compute
these marginals when the underlying graph is a tree, has gained its popularity
as an efficient way to approximate them in the more general case. In this
paper, we focus on an aspect of the algorithm that did not get that much
attention in the literature, which is the effect of the normalization of the
messages. We show in particular that, for a large class of normalization
strategies, it is possible to focus only on belief convergence. Following this,
we express the necessary and sufficient conditions for local stability of a
fixed point in terms of the graph structure and the beliefs values at the fixed
point. We also explicit some connexion between the normalization constants and
the underlying Bethe Free Energy.
|
1101.4204
|
Measuring Performance of Continuous-Time Stochastic Processes using
Timed Automata
|
cs.SY cs.FL
|
We propose deterministic timed automata (DTA) as a model-independent language
for specifying performance and dependability measures over continuous-time
stochastic processes. Technically, these measures are defined as limit
frequencies of locations (control states) of a DTA that observes computations
of a given stochastic process. Then, we study the properties of DTA measures
over semi-Markov processes in greater detail. We show that DTA measures over
semi-Markov processes are well-defined with probability one, and there are only
finitely many values that can be assumed by these measures with positive
probability. We also give an algorithm which approximates these values and the
associated probabilities up to an arbitrarily small given precision. Thus, we
obtain a general and effective framework for analysing DTA measures over
semi-Markov processes.
|
1101.4207
|
Blind Channel Estimation for Amplify-and-Forward Two-Way Relay Networks
Employing M-PSK Modulation
|
cs.IT math.IT stat.OT
|
We consider the problem of channel estimation for amplify-and-forward (AF)
two-way relay networks (TWRNs). Most works on this problem focus on pilot-based
approaches which impose a significant training overhead that reduces the
spectral efficiency of the system. To avoid such losses, this work proposes
blind channel estimation algorithms for AF TWRNs that employ constant-modulus
(CM) signaling. Our main algorithm is based on the deterministic maximum
likelihood (DML) approach. Assuming M-PSK modulation, we show that the
resulting estimator is consistent and approaches the true channel with high
probability at high SNR for modulation orders higher than 2. For BPSK, however,
the DML performs poorly and we propose an alternative algorithm that performs
much better by taking into account the BPSK structure of the data symbols. For
comparative purposes, we also investigate the Gaussian maximum-likelihood (GML)
approach which treats the data symbols as Gaussian-distributed nuisance
parameters. We derive the Cramer-Rao bound and use Monte-Carlo simulations to
investigate the mean squared error (MSE) performance of the proposed
algorithms. We also compare the symbol-error rate (SER) performance of the DML
algorithm with that of the training-based least-squares (LS) algorithm and
demonstrate that the DML offers a superior tradeoff between accuracy and
spectral efficiency.
|
1101.4211
|
Throughput-optimal Scheduling in Multi-hop Wireless Networks without
Per-flow Information
|
cs.NI cs.IT cs.PF math.IT
|
In this paper, we consider the problem of link scheduling in multi-hop
wireless networks under general interference constraints. Our goal is to design
scheduling schemes that do not use per-flow or per-destination information,
maintain a single data queue for each link, and exploit only local information,
while guaranteeing throughput optimality. Although the celebrated back-pressure
algorithm maximizes throughput, it requires per-flow or per-destination
information. It is usually difficult to obtain and maintain this type of
information, especially in large networks, where there are numerous flows.
Also, the back-pressure algorithm maintains a complex data structure at each
node, keeps exchanging queue length information among neighboring nodes, and
commonly results in poor delay performance. In this paper, we propose
scheduling schemes that can circumvent these drawbacks and guarantee throughput
optimality. These schemes use either the readily available hop-count
information or only the local information for each link. We rigorously analyze
the performance of the proposed schemes using fluid limit techniques via an
inductive argument and show that they are throughput-optimal. We also conduct
simulations to validate our theoretical results in various settings, and show
that the proposed schemes can substantially improve the delay performance in
most scenarios.
|
1101.4227
|
Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs
|
physics.data-an cond-mat.dis-nn cond-mat.stat-mech cs.LG
|
We theoretically study semi-supervised clustering in sparse graphs in the
presence of pairwise constraints on the cluster assignments of nodes. We focus
on bi-cluster graphs, and study the impact of semi-supervision for varying
constraint density and overlap between the clusters. Recent results for
unsupervised clustering in sparse graphs indicate that there is a critical
ratio of within-cluster and between-cluster connectivities below which clusters
cannot be recovered with better than random accuracy. The goal of this paper is
to examine the impact of pairwise constraints on the clustering accuracy. Our
results suggests that the addition of constraints does not provide automatic
improvement over the unsupervised case. When the density of the constraints is
sufficiently small, their only impact is to shift the detection threshold while
preserving the criticality. Conversely, if the density of (hard) constraints is
above the percolation threshold, the criticality is suppressed and the
detection threshold disappears.
|
1101.4270
|
A Comparative Agglomerative Hierarchical Clustering Method to Cluster
Implemented Course
|
cs.DB
|
There are many clustering methods, such as hierarchical clustering method.
Most of the approaches to the clustering of variables encountered in the
literature are of hierarchical type. The great majority of hierarchical
approaches to the clustering of variables are of agglomerative nature. The
agglomerative hierarchical approach to clustering starts with each observation
as its own cluster and then continually groups the observations into
increasingly larger groups. Higher Learning Institution (HLI) provides training
to introduce final-year students to the real working environment. In this
research will use Euclidean single linkage and complete linkage. MATLAB and HCE
3.5 software will used to train data and cluster course implemented during
industrial training. This study indicates that different method will create a
different number of clusters.
|
1101.4279
|
Low-Complexity Detection/Equalization in Large-Dimension MIMO-ISI
Channels Using Graphical Models
|
cs.IT math.IT
|
In this paper, we deal with low-complexity near-optimal
detection/equalization in large-dimension multiple-input multiple-output
inter-symbol interference (MIMO-ISI) channels using message passing on
graphical models. A key contribution in the paper is the demonstration that
near-optimal performance in MIMO-ISI channels with large dimensions can be
achieved at low complexities through simple yet effective
simplifications/approximations, although the graphical models that represent
MIMO-ISI channels are fully/densely connected (loopy graphs). These include 1)
use of Markov Random Field (MRF) based graphical model with pairwise
interaction, in conjunction with {\em message/belief damping}, and 2) use of
Factor Graph (FG) based graphical model with {\em Gaussian approximation of
interference} (GAI). The per-symbol complexities are $O(K^2n_t^2)$ and
$O(Kn_t)$ for the MRF and the FG with GAI approaches, respectively, where $K$
and $n_t$ denote the number of channel uses per frame, and number of transmit
antennas, respectively. These low-complexities are quite attractive for large
dimensions, i.e., for large $Kn_t$. From a performance perspective, these
algorithms are even more interesting in large-dimensions since they achieve
increasingly closer to optimum detection performance for increasing $Kn_t$.
Also, we show that these message passing algorithms can be used in an iterative
manner with local neighborhood search algorithms to improve the
reliability/performance of $M$-QAM symbol detection.
|
1101.4285
|
Degree and connectivity of the Internet's scale-free topology
|
cs.NI cs.SI physics.soc-ph
|
In this paper we theoretically and empirically study the degree and
connectivity of the Internet's scale-free topology at the autonomous system
(AS) level. The basic features of the scale-free network have influence on the
normalization constant of the degree distribution p(k). We develop a
mathematics model of the Internet's scale-free topology. On this model we
theoretically get the formulas of the average degree, the ratios of the
kmin-degree (minimum degree) nodes and the kmax-degree (maximum degree) nodes,
the fraction of the degrees (or links) in the hands of the richer (top
best-connected) nodes. We find the average degree is larger for smaller
power-law exponent {\lambda} and larger minimum or maximum degree. The ratio of
the kmin-degree nodes is larger for larger {\lambda} and smaller kmin or kmax.
The ratio of the kmax-degree ones is larger for smaller {\lambda} and kmax or
larger kmin. The richer nodes hold most of the total degrees of the AS-level
Internet topology. In addition, we reveal the ratio of the kmin-degree nodes or
the rate of the increase of the average degree has power-law decay with the
increase of the kmin. The ratio of the kmax-degree nodes has power-law decay
with the increase of the kmax, and the fraction of the degrees in the hands of
the richer 27% nodes is about 73% (the '73/27 rule'). At last, we empirically
calculate, based on empirical data extracted from BGP, the average degree and
the ratio and fraction using our method and other methods, and find that our
method is rigorous and effective for the AS-level Internet topology.
|
1101.4301
|
Diffusion framework for geometric and photometric data fusion in
non-rigid shape analysis
|
cs.CV
|
In this paper, we explore the use of the diffusion geometry framework for the
fusion of geometric and photometric information in local and global shape
descriptors. Our construction is based on the definition of a diffusion process
on the shape manifold embedded into a high-dimensional space where the
embedding coordinates represent the photometric information. Experimental
results show that such data fusion is useful in coping with different
challenges of shape analysis where pure geometric and pure photometric methods
fail.
|
1101.4313
|
A weak spectral condition for the controllability of the bilinear
Schr\"odinger equation with application to the control of a rotating planar
molecule
|
math.OC cs.SY math.AP
|
In this paper we prove an approximate controllability result for the bilinear
Schr\"odinger equation. This result requires less restrictive non-resonance
hypotheses on the spectrum of the uncontrolled Schr\"odinger operator than
those present in the literature. The control operator is not required to be
bounded and we are able to extend the controllability result to the density
matrices. The proof is based on fine controllability properties of the finite
dimensional Galerkin approximations and allows to get estimates for the $L^{1}$
norm of the control. The general controllability result is applied to the
problem of controlling the rotation of a bipolar rigid molecule confined on a
plane by means of two orthogonal external fields.
|
1101.4335
|
Peak Reduction and Clipping Mitigation by Compressive Sensing
|
cs.IT math.IT math.ST stat.TH
|
This work establishes the design, analysis, and fine-tuning of a
Peak-to-Average-Power-Ratio (PAPR) reducing system, based on compressed sensing
at the receiver of a peak-reducing sparse clipper applied to an OFDM signal at
the transmitter. By exploiting the sparsity of the OFDM signal in the time
domain relative to a pre-defined clipping threshold, the method depends on
partially observing the frequency content of extremely simple sparse clippers
to recover the locations, magnitudes, and phases of the clipped coefficients of
the peak-reduced signal. We claim that in the absence of optimization
algorithms at the transmitter that confine the frequency support of clippers to
a predefined set of reserved-tones, no other tone-reservation method can
reliably recover the original OFDM signal with such low complexity.
Afterwards we focus on designing different clipping signals that can embed a
priori information regarding the support and phase of the peak-reducing signal
to the receiver, followed by modified compressive sensing techniques for
enhanced recovery. This includes data-based weighted {\ell} 1 minimization for
enhanced support recovery and phase-augmention for homogeneous clippers
followed by Bayesian techniques.
We show that using such techniques for a typical OFDM signal of 256
subcarriers and 20% reserved tones, the PAPR can be reduced by approximately
4.5 dB with a significant increase in capacity compared to a system which uses
all its tones for data transmission and clips to such levels. The design is
hence appealing from both capacity and PAPR reduction aspects.
|
1101.4343
|
Fundamental Tradeoffs on Green Wireless Networks
|
cs.IT math.IT
|
Traditional design of mobile wireless networks mainly focuses on ubiquitous
access and large capacity. However, as energy saving and environmental
protection become a global demand and inevitable trend, wireless researchers
and engineers need to shift their focus to energy-efficiency oriented design,
that is, green radio. In this paper, we propose a framework for green radio
research and integrate the fundamental issues that are currently scattered. The
skeleton of the framework consists of four fundamental tradeoffs: deployment
efficiency - energy efficiency tradeoff, spectrum efficiency - energy
efficiency tradeoff, bandwidth - power tradeoff, and delay - power tradeoff.
With the help of the four fundamental tradeoffs, we demonstrate that key
network performance/cost indicators are all stringed together.
|
1101.4351
|
Building a Chaotic Proved Neural Network
|
cs.AI cs.CR math.DS math.GN
|
Chaotic neural networks have received a great deal of attention these last
years. In this paper we establish a precise correspondence between the
so-called chaotic iterations and a particular class of artificial neural
networks: global recurrent multi-layer perceptrons. We show formally that it is
possible to make these iterations behave chaotically, as defined by Devaney,
and thus we obtain the first neural networks proven chaotic. Several neural
networks with different architectures are trained to exhibit a chaotical
behavior.
|
1101.4356
|
Meaning Negotiation as Inference
|
cs.AI
|
Meaning negotiation (MN) is the general process with which agents reach an
agreement about the meaning of a set of terms. Artificial Intelligence scholars
have dealt with the problem of MN by means of argumentations schemes, beliefs
merging and information fusion operators, and ontology alignment but the
proposed approaches depend upon the number of participants. In this paper, we
give a general model of MN for an arbitrary number of agents, in which each
participant discusses with the others her viewpoint by exhibiting it in an
actual set of constraints on the meaning of the negotiated terms. We call this
presentation of individual viewpoints an angle. The agents do not aim at
forming a common viewpoint but, instead, at agreeing about an acceptable common
angle. We analyze separately the process of MN by two agents (\emph{bilateral}
or \emph{pairwise} MN) and by more than two agents (\emph{multiparty} MN), and
we use game theoretic models to understand how the process develops in both
cases: the models are Bargaining Game for bilateral MN and English Auction for
multiparty MN. We formalize the process of reaching such an agreement by giving
a deduction system that comprises of rules that are consistent and adequate for
representing MN.
|
1101.4372
|
Order Optimal Information Spreading Using Algebraic Gossip
|
cs.IT cs.DC cs.NI math.IT
|
In this paper we study gossip based information spreading with bounded
message sizes. We use algebraic gossip to disseminate $k$ distinct messages to
all $n$ nodes in a network. For arbitrary networks we provide a new upper bound
for uniform algebraic gossip of $O((k+\log n + D)\Delta)$ rounds with high
probability, where $D$ and $\Delta$ are the diameter and the maximum degree in
the network, respectively. For many topologies and selections of $k$ this bound
improves previous results, in particular, for graphs with a constant maximum
degree it implies that uniform gossip is \emph{order optimal} and the stopping
time is $\Theta(k + D)$.
To eliminate the factor of $\Delta$ from the upper bound we propose a
non-uniform gossip protocol, TAG, which is based on algebraic gossip and an
arbitrary spanning tree protocol $\S$. The stopping time of TAG is $O(k+\log n
+d(\S)+t(\S))$, where $t(\S)$ is the stopping time of the spanning tree
protocol, and $d(\S)$ is the diameter of the spanning tree. We provide two
general cases in which this bound leads to an order optimal protocol. The first
is for $k=\Omega(n)$, where, using a simple gossip broadcast protocol that
creates a spanning tree in at most linear time, we show that TAG finishes after
$\Theta(n)$ rounds for any graph. The second uses a sophisticated, recent
gossip protocol to build a fast spanning tree on graphs with large weak
conductance. In turn, this leads to the optimally of TAG on these graphs for
$k=\Omega(\mathrm{polylog}(n))$. The technique used in our proofs relies on
queuing theory, which is an interesting approach that can be useful in future
gossip analysis.
|
1101.4373
|
Statistical Multiresolution Dantzig Estimation in Imaging: Fundamental
Concepts and Algorithmic Framework
|
stat.AP cs.CV cs.SY math.OC stat.CO
|
In this paper we are concerned with fully automatic and locally adaptive
estimation of functions in a "signal + noise"-model where the regression
function may additionally be blurred by a linear operator, e.g. by a
convolution. To this end, we introduce a general class of statistical
multiresolution estimators and develop an algorithmic framework for computing
those. By this we mean estimators that are defined as solutions of convex
optimization problems with supremum-type constraints. We employ a combination
of the alternating direction method of multipliers with Dykstra's algorithm for
computing orthogonal projections onto intersections of convex sets and prove
numerical convergence. The capability of the proposed method is illustrated by
various examples from imaging and signal detection.
|
1101.4378
|
Cycles of cooperation and defection in imperfect learning
|
physics.soc-ph cs.SI nlin.AO
|
When people play a repeated game they usually try to anticipate their
opponents' moves based on past observations, and then decide what action to
take next. Behavioural economics studies the mechanisms by which strategic
decisions are taken in these adaptive learning processes. We here investigate a
model of learning the iterated prisoner's dilemma game. Players have the choice
between three strategies, always defect (ALLD), always cooperate (ALLC) and
tit-for-tat (TFT). The only strict Nash equilibrium in this situation is ALLD.
When players learn to play this game convergence to the equilibrium is not
guaranteed, for example we find cooperative behaviour if players discount
observations in the distant past. When agents use small samples of observed
moves to estimate their opponent's strategy the learning process is stochastic,
and sustained oscillations between cooperation and defection can emerge. These
cycles are similar to those found in stochastic evolutionary processes, but the
origin of the noise sustaining the oscillations is different and lies in the
imperfect sampling of the opponent's strategy. Based on a systematic expansion
technique, we are able to predict the properties of these learning cycles,
providing an analytical tool with which the outcome of more general stochastic
adaptation processes can be characterised.
|
1101.4388
|
Reproducing Kernel Banach Spaces with the l1 Norm
|
stat.ML cs.LG math.FA
|
Targeting at sparse learning, we construct Banach spaces B of functions on an
input space X with the properties that (1) B possesses an l1 norm in the sense
that it is isometrically isomorphic to the Banach space of integrable functions
on X with respect to the counting measure; (2) point evaluations are continuous
linear functionals on B and are representable through a bilinear form with a
kernel function; (3) regularized learning schemes on B satisfy the linear
representer theorem. Examples of kernel functions admissible for the
construction of such spaces are given.
|
1101.4431
|
Parameter Optimization of Multi-Agent Formations based on LQR Design
|
cs.SY cs.MA
|
In this paper we study the optimal formation control of multiple agents whose
interaction parameters are adjusted upon a cost function consisting of both the
control energy and the geometrical performance. By optimizing the interaction
parameters and by the linear quadratic regulation(LQR) controllers, the upper
bound of the cost function is minimized. For systems with homogeneous agents
interconnected over sparse graphs, distributed controllers are proposed that
inherit the same underlying graph as the one among agents. For the more general
case, a relaxed optimization problem is considered so as to eliminate the
nonlinear constraints. Using the subgradient method, interaction parameters
among agents are optimized under the constraint of a sparse graph, and the
optimum of the cost function is a better result than the one when agents
interacted only through the control channel. Numerical examples are provided to
validate the effectiveness of the method and to illustrate the geometrical
performance of the system.
|
1101.4435
|
Solutions for the MIMO Gaussian Wiretap Channel with a Cooperative
Jammer
|
cs.IT math.IT
|
We study the Gaussian MIMO wiretap channel with a transmitter, a legitimate
receiver, an eavesdropper and an external helper, each equipped with multiple
antennas. The transmitter sends confidential messages to its intended receiver,
while the helper transmits jamming signals independent of the source message to
confuse the eavesdropper. The jamming signal is assumed to be treated as noise
at both the intended receiver and the eavesdropper. We obtain a closed-form
expression for the structure of the artificial noise covariance matrix that
guarantees no decrease in the secrecy capacity of the wiretap channel. We also
describe how to find specific realizations of this covariance matrix expression
that provide good secrecy rate performance, even when there is no non-trivial
null space between the helper and the intended receiver. Unlike prior work, our
approach considers the general MIMO case, and is not restricted to SISO or MISO
scenarios.
|
1101.4439
|
Reproducing Kernel Banach Spaces with the l1 Norm II: Error Analysis for
Regularized Least Square Regression
|
stat.ML cs.LG math.FA
|
A typical approach in estimating the learning rate of a regularized learning
scheme is to bound the approximation error by the sum of the sampling error,
the hypothesis error and the regularization error. Using a reproducing kernel
space that satisfies the linear representer theorem brings the advantage of
discarding the hypothesis error from the sum automatically. Following this
direction, we illustrate how reproducing kernel Banach spaces with the l1 norm
can be applied to improve the learning rate estimate of l1-regularization in
machine learning.
|
1101.4445
|
Spectrum Management for Cognitive Radio based on Genetics Algorithm
|
cs.NE
|
Spectrum scarceness is one of the major challenges that the present world is
facing. The efficient use of existing licensed spectrum is becoming most
critical as growing demand of the radio spectrum. Different researches show
that the use of licensed are not utilized inefficiently. It has been also shown
that primary user does not use more than 70% of the licensed frequency band
most of the time. Many researchers are trying to found the techniques that
efficiently utilize the under-utilized licensed spectrum. One of the approaches
is the use of "Cognitive Radio". This allows the radio to learn from its
environment, changing certain parameters. Based on this knowledge the radio can
dynamically exploit the spectrum holes in the licensed band of the spectrum.
This paper w i l l focus on the performance of spectrum allocation technique,
based on popular meta-heuristics Genetics Algorithm and analyzing the
performance of this technique using Mat Lab.
|
1101.4450
|
Adaptive Submodular Optimization under Matroid Constraints
|
cs.DS cs.AI
|
Many important problems in discrete optimization require maximization of a
monotonic submodular function subject to matroid constraints. For these
problems, a simple greedy algorithm is guaranteed to obtain near-optimal
solutions. In this article, we extend this classic result to a general class of
adaptive optimization problems under partial observability, where each choice
can depend on observations resulting from past choices. Specifically, we prove
that a natural adaptive greedy algorithm provides a $1/(p+1)$ approximation for
the problem of maximizing an adaptive monotone submodular function subject to
$p$ matroid constraints, and more generally over arbitrary $p$-independence
systems. We illustrate the usefulness of our result on a complex adaptive
match-making application.
|
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