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1202.0535
|
List decoding subspace codes from insertions and deletions
|
cs.IT cs.CC math.IT
|
We present a construction of subspace codes along with an efficient algorithm
for list decoding from both insertions and deletions, handling an
information-theoretically maximum fraction of these with polynomially small
rate. Our construction is based on a variant of the folded Reed-Solomon codes
in the world of linearized polynomials, and the algorithm is inspired by the
recent linear-algebraic approach to list decoding. Ours is the first list
decoding algorithm for subspace codes that can handle deletions; even one
deletion can totally distort the structure of the basis of a subspace and is
thus challenging to handle. When there are only insertions, we also present
results for list decoding subspace codes that are the linearized analog of
Reed-Solomon codes (proposed previously, and closely related to the Gabidulin
codes for rank-metric), obtaining some improvements over similar results in
previous work.
|
1202.0536
|
An Outer Bound for the Vector Gaussian CEO Problem
|
cs.IT math.IT
|
We study the vector Gaussian CEO problem, where there are an arbitrary number
of agents each having a noisy observation of a vector Gaussian source. The goal
of the agents is to describe the source to a central unit, which wants to
reconstruct the source within a given distortion. The rate-distortion region of
the vector Gaussian CEO problem is unknown in general. Here, we provide an
outer bound for the rate-distortion region of the vector Gaussian CEO problem.
We obtain our outer bound by evaluating an outer bound for the multi-terminal
source coding problem by means of a technique relying on the de Bruijn identity
and the properties of the Fisher information. Next, we show that our outer
bound strictly improves upon the existing outer bounds for all system
parameters. We show this strict improvement by providing a specific example,
and showing that there exists a gap between our outer bound and the existing
outer bounds. Although our outer bound improves upon the existing outer bounds,
we show that our outer bound does not provide the exact rate-distortion region
in general. To this end, we provide an example and show that the
rate-distortion region is strictly contained in our outer bound for this
example.
|
1202.0549
|
Comparing Background Subtraction Algorithms and Method of Car Counting
|
cs.CV
|
In this paper, we compare various image background subtraction algorithms
with the ground truth of cars counted. We have given a sample of thousand
images, which are the snap shots of current traffic as records at various
intersections and highways. We have also counted an approximate number of cars
that are visible in these images. In order to ascertain the accuracy of
algorithms to be used for the processing of million images, we compare them on
many metrics that includes (i) Scalability (ii) Accuracy (iii) Processing time.
|
1202.0568
|
Acoustic Communication for Medical Nanorobots
|
cs.RO physics.bio-ph physics.med-ph
|
Communication among microscopic robots (nanorobots) can coordinate their
activities for biomedical tasks. The feasibility of in vivo ultrasonic
communication is evaluated for micron-size robots broadcasting into various
types of tissues. Frequencies between 10MHz and 300MHz give the best tradeoff
between efficient acoustic generation and attenuation for communication over
distances of about 100 microns. Based on these results, we find power available
from ambient oxygen and glucose in the bloodstream can readily support
communication rates of about 10,000 bits/second between micron-sized robots. We
discuss techniques, such as directional acoustic beams, that can increase this
rate. The acoustic pressure fields enabling this communication are unlikely to
damage nearby tissue, and short bursts at considerably higher power could be of
therapeutic use.
|
1202.0589
|
Min-max fair coordinated beamforming in cellular systems via large
systems analysis
|
cs.IT math.IT
|
This paper considers base station (BS) cooperation in the form of coordinated
beamforming, focusing on min-max fairness in the power usage subject to target
SINR constraints. We show that the optimal beamforming strategies have an
interesting nested zero-forcing structure. In the asymptotic regime where the
number of antennas at each BS and the number of users in each cell both grow
large with their ratio tending to a finite constant, the dimensionality of the
optimization is greatly reduced, and only knowledge of statistics is required
to solve it. The optimal solution is characterized in general, and an algorithm
is proposed that converges to the optimal transmit parameters, for feasible
SINR targets. For the two cell case, a simple single parameter characterization
is obtained. These asymptotic results provide insights into the average
performance, as well as simple but efficient beamforming strategies for the
finite system case. In particular, the optimal beamforming strategy from the
large systems analysis only requires the base stations to have local
instantaneous channel state information; the remaining parameters of the
beamformer can be calculated using channel statistics which can easily be
shared amongst the base stations.
|
1202.0592
|
On Parameterized Gallager's First Bounds for Binary Linear Codes over
AWGN Channels
|
cs.IT math.IT
|
In this paper, nested Gallager regions with a single parameter is introduced
to exploit Gallager's first bounding technique (GFBT). We present a necessary
and sufficient condition on the optimal parameter. We also present a sufficient
condition (with a simple geometrical explanation) under which the optimal
parameter does not depend on the signal-to-noise ratio (SNR). With this general
framework, three existing upper bounds are revisited, including the tangential
bound (TB) of Berlekamp, the sphere bound (SB) of Herzberg and Poltyrev, and
the tangential-sphere bound (TSB) of Poltyrev. This paper also reveals that the
SB of Herzberg and Poltyrev is equivalent to the SB of Kasami et al., which was
rarely cited in literature.
|
1202.0601
|
Precise evaluation of leaked information with universal2 privacy
amplification in the presence of quantum attacker
|
quant-ph cs.CR cs.IT math.IT
|
We treat secret key extraction when the eavesdropper has correlated quantum
states. We propose quantum privacy amplification theorems different from
Renner's, which are based on quantum conditional R\'{e}nyi entropy of order
1+s. Using those theorems, we derive an exponential decreasing rate for leaked
information and the asymptotic equivocation rate, which have not been derived
hitherto in the quantum setting.
|
1202.0607
|
On the Alternative Relaying Diamond Channel with Conferencing Links
|
cs.IT math.IT
|
In this paper, the diamond relay channel is considered, which consists of one
source-destination pair and two relay nodes connected with rate-limited
out-of-band conferencing links. In particular, we focus on the half-duplex
alternative relaying strategy, in which the two relays operate alternatively
over time. With different amounts of delay, two conferencing strategies are
proposed, each of which can be implemented by either a general two-side
conferencing scheme (for which both of the two conferencing links are used) or
a special-case one-side conferencing scheme (for which only one of the two
conferencing links is used). Based on the most general two-side conferencing
scheme, we derive the achievable rates by using the decode-and-forward (DF) and
amplify-and-forward (AF) relaying schemes, and show that these rate
maximization problems are convex. By further exploiting the properties of the
optimal solutions, the simpler one-side conferencing is shown to be equally
good as the two-side conferencing in term of the achievable rates under
arbitrary channel conditions. Based on this, the DF rate in closed-form is
obtained, and the principle to use which one of the two conferencing links for
one-side conferencing is also established. Moreover, the DF scheme is shown to
be capacity-achieving under certain conditions with even one-side conferencing.
For the AF relaying scheme, one-side conferencing is shown to be sub-optimal in
general. Finally, numerical results are provided to validate our analysis.
|
1202.0609
|
Wavelet-based deconvolution of ultrasonic signals in nondestructive
evaluation
|
cs.CV
|
In this paper, the inverse problem of reconstructing reflectivity function of
a medium is examined within a blind deconvolution framework. The ultrasound
pulse is estimated using higher-order statistics, and Wiener filter is used to
obtain the ultrasonic reflectivity function through wavelet-based models. A new
approach to the parameter estimation of the inverse filtering step is proposed
in the nondestructive evaluation field, which is based on the theory of
Fourier-Wavelet regularized deconvolution (ForWaRD). This new approach can be
viewed as a solution to the open problem of adaptation of the ForWaRD framework
to perform the convolution kernel estimation and deconvolution
interdependently. The results indicate stable solutions of the estimated pulse
and an improvement in the radio-frequency (RF) signal taking into account its
signal-to-noise ratio (SNR) and axial resolution. Simulations and experiments
showed that the proposed approach can provide robust and optimal estimates of
the reflectivity function.
|
1202.0617
|
Classification of Flames in Computer Mediated Communications
|
cs.SI cs.CL
|
Computer Mediated Communication (CMC) has brought about a revolution in the
way the world communicates with each other. With the increasing number of
people, interacting through the internet and the rise of new platforms and
technologies has brought together the people from different social, cultural
and geographical backgrounds to present their thoughts, ideas and opinions on
topics of their interest. CMC has, in some cases, gave users more freedom to
express themselves as compared to Face-to-face communication. This has also led
to rise in the use of hostile and aggressive language and terminologies
uninhibitedly. Since such use of language is detrimental to the discussion
process and affects the audience and individuals negatively, efforts are being
taken to control them. The research sees the need to understand the concept of
flaming and hence attempts to classify them in order to give a better
understanding of it. The classification is done on the basis of type of flame
content being presented and the Style in which they are presented.
|
1202.0621
|
New Geometrical Spectra of Linear Codes with Applications to Performance
Analysis
|
cs.IT math.IT
|
In this paper, new enumerating functions for linear codes are defined,
including the triangle enumerating function and the tetrahedron enumerating
function, both of which can be computed using a trellis-based algorithm over
polynomial rings. The computational complexity is dominated by the complexity
of the trellis. In addition, we show that these new enumerating functions can
be used to improve existing performance bounds on the maximum likelihood
decoding.
|
1202.0655
|
Central Approximation in Statistical Physics and Information Theory
|
cs.IT cond-mat.stat-mech math.IT
|
In statistical physics and information theory, although the exponent of the
partition function is often of our primary interest, there are cases where one
needs more detailed information. In this paper, we present a general framework
to study more precise asymptotic behaviors of the partition function, using the
central approximation in conjunction with the method of types.
|
1202.0666
|
Generalized minimizers of convex integral functionals, Bregman distance,
Pythagorean identities
|
math.OC cs.IT math.IT math.PR math.ST stat.TH
|
Integral functionals based on convex normal integrands are minimized subject
to finitely many moment constraints. The integrands are finite on the positive
and infinite on the negative numbers, strictly convex but not necessarily
differentiable. The minimization is viewed as a primal problem and studied
together with a dual one in the framework of convex duality. The effective
domain of the value function is described by a conic core, a modification of
the earlier concept of convex core. Minimizers and generalized minimizers are
explicitly constructed from solutions of modified dual problems, not assuming
the primal constraint qualification. A generalized Pythagorean identity is
presented using Bregman distance and a correction term for lack of essential
smoothness in integrands. Results are applied to minimization of Bregman
distances. Existence of a generalized dual solution is established whenever the
dual value is finite, assuming the dual constraint qualification. Examples of
`irregular' situations are included, pointing to the limitations of generality
of certain key results.
|
1202.0675
|
Construction of MIMO MAC Codes Achieving the Pigeon Hole Bound
|
math.RA cs.IT math.IT
|
This paper provides a general construction method for multiple-input
multiple-output multiple access channel codes (MIMO MAC codes) that have so
called generalized full rank property. The achieved constructions give a
positive answer to the question whether it is generally possible to reach the
so called pigeon hole bound, that is an upper bound for the decay of
determinants of MIMO-MAC channel codes.
|
1202.0678
|
Influence of Topological Features on Spatially-Structured Evolutionary
Algorithms Dynamics
|
cs.NE
|
In the last decades, complex networks theory significantly influenced other
disciplines on the modeling of both static and dynamic aspects of systems
observed in nature. This work aims to investigate the effects of networks'
topological features on the dynamics of an evolutionary algorithm, considering
in particular the ability to find a large number of optima on multi-modal
problems. We introduce a novel spatially-structured evolutionary algorithm and
we apply it on two combinatorial problems: ONEMAX and the multi-modal NMAX.
Considering three different network models we investigate the relationships
between their features, algorithm's convergence and its ability to find
multiple optima (for the multi-modal problem). In order to perform a deeper
analysis we investigate the introduction of weighted graphs with time-varying
weights. The results show that networks with a large Average Path Length lead
to an higher number of optima and a consequent slow exploration dynamics (i.e.
low First Hitting Time). Furthermore, the introduction of weighted networks
shows the possibility to tune algorithm's dynamics during its execution with
the parameter related with weights' change. This work gives a first answer
about the effects of various graph topologies on the diversity of evolutionary
algorithms and it describes a simple but powerful algorithmic framework which
allows to investigate many aspects of ssEAs dynamics.
|
1202.0690
|
Minimization of Transmission Duration of Data Packets over an Energy
Harvesting Fading Channel
|
cs.IT math.IT
|
The offline problem of transmission completion time minimization for an
energy harvesting transmitter under fading is extended to allow packet arrivals
during transmission. A method for computing an optimal power and rate
allocation (i.e., an optimal offline schedule) is developed and studied.
|
1202.0702
|
Low-Density Arrays of Circulant Matrices: Rank and Row-Redundancy
Analysis, and Quasi-Cyclic LDPC Codes
|
cs.IT math.IT
|
This paper is concerned with general analysis on the rank and row-redundancy
of an array of circulants whose null space defines a QC-LDPC code. Based on the
Fourier transform and the properties of conjugacy classes and Hadamard products
of matrices, we derive tight upper bounds on rank and row-redundancy for
general array of circulants, which make it possible to consider row-redundancy
in constructions of QC-LDPC codes to achieve better performance. We further
investigate the rank of two types of construction of QC-LDPC codes:
constructions based on Vandermonde Matrices and Latin Squares and give
combinatorial expression of the exact rank in some specific cases, which
demonstrates the tightness of the bound we derive. Moreover, several types of
new construction of QC-LDPC codes with large row-redundancy are presented and
analyzed.
|
1202.0747
|
A Graph Theoretical Approach to Network Encoding Complexity
|
cs.IT math.IT
|
Consider an acyclic directed network $G$ with sources $S_1, S_2,..., S_l$ and
distinct sinks $R_1, R_2,..., R_l$. For $i=1, 2,..., l$, let $c_i$ denote the
min-cut between $S_i$ and $R_i$. Then, by Menger's theorem, there exists a
group of $c_i$ edge-disjoint paths from $S_i$ to $R_i$, which will be referred
to as a group of Menger's paths from $S_i$ to $R_i$ in this paper. Although
within the same group they are edge-disjoint, the Menger's paths from different
groups may have to merge with each other. It is known that by choosing Menger's
paths appropriately, the number of mergings among different groups of Menger's
paths is always bounded by a constant, which is independent of the size and the
topology of $G$. The tightest such constant for the all the above-mentioned
networks is denoted by $\mathcal{M}(c_1, c_2,..., c_2)$ when all $S_i$'s are
distinct, and by $\mathcal{M}^*(c_1, c_2,..., c_2)$ when all $S_i$'s are in
fact identical. It turns out that $\mathcal{M}$ and $\mathcal{M}^*$ are closely
related to the network encoding complexity for a variety of networks, such as
multicast networks, two-way networks and networks with multiple sessions of
unicast. Using this connection, we compute in this paper some exact values and
bounds in network encoding complexity using a graph theoretical approach.
|
1202.0753
|
Simulation of stochastic systems via polynomial chaos expansions and
convex optimization
|
stat.CO cs.SY math-ph math.DS math.MP math.OC
|
Polynomial Chaos Expansions represent a powerful tool to simulate stochastic
models of dynamical systems. Yet, deriving the expansion's coefficients for
complex systems might require a significant and non-trivial manipulation of the
model, or the computation of large numbers of simulation runs, rendering the
approach too time consuming and impracticable for applications with more than a
handful of random variables. We introduce a novel computationally tractable
technique for computing the coefficients of polynomial chaos expansions. The
approach exploits a regularization technique with a particular choice of
weighting matrices, which allow to take into account the specific features of
Polynomial Chaos expansions. The method, completely based on convex
optimization, can be applied to problems with a large number of random
variables and uses a modest number of Monte Carlo simulations, while avoiding
model manipulations. Additional information on the stochastic process, when
available, can be also incorporated in the approach by means of convex
constraints. We show the effectiveness of the proposed technique in three
applications in diverse fields, including the analysis of a nonlinear electric
circuit, a chaotic model of organizational behavior, finally a chemical
oscillator.
|
1202.0754
|
On the Exact Distribution of the Scaled Largest Eigenvalue
|
cs.IT math.IT
|
In this paper we study the distribution of the scaled largest eigenvalue of
complexWishart matrices, which has diverse applications both in statistics and
wireless communications. Exact expressions, valid for any matrix dimensions,
have been derived for the probability density function and the cumulative
distribution function. The derived results involve only finite sums of
polynomials. These results are obtained by taking advantage of properties of
the Mellin transform for products of independent random variables.
|
1202.0773
|
Capacities of classical compound quantum wiretap and classical quantum
compound wiretap channels
|
quant-ph cs.IT math.IT
|
We determine the capacity of the classical compound quantum wiretapper
channel with channel state information at the transmitter. Moreover we derive a
lower bound on the capacity of this channel without channel state information
and determine the capacity of the classical quantum compound wiretap channel
with channel state information at the transmitter.
|
1202.0786
|
Minimax Rates of Estimation for Sparse PCA in High Dimensions
|
stat.ML cs.LG math.ST stat.TH
|
We study sparse principal components analysis in the high-dimensional
setting, where $p$ (the number of variables) can be much larger than $n$ (the
number of observations). We prove optimal, non-asymptotic lower and upper
bounds on the minimax estimation error for the leading eigenvector when it
belongs to an $\ell_q$ ball for $q \in [0,1]$. Our bounds are sharp in $p$ and
$n$ for all $q \in [0, 1]$ over a wide class of distributions. The upper bound
is obtained by analyzing the performance of $\ell_q$-constrained PCA. In
particular, our results provide convergence rates for $\ell_1$-constrained PCA.
|
1202.0796
|
Efficient Controller Synthesis for Consumption Games with Multiple
Resource Types
|
cs.GT cs.SY math.OC
|
We introduce consumption games, a model for discrete interactive system with
multiple resources that are consumed or reloaded independently. More precisely,
a consumption game is a finite-state graph where each transition is labeled by
a vector of resource updates, where every update is a non-positive number or
omega. The omega updates model the reloading of a given resource. Each vertex
belongs either to player \Box or player \Diamond, where the aim of player \Box
is to play so that the resources are never exhausted. We consider several
natural algorithmic problems about consumption games, and show that although
these problems are computationally hard in general, they are solvable in
polynomial time for every fixed number of resource types (i.e., the dimension
of the update vectors).
|
1202.0798
|
On Coding Efficiency for Flash Memories
|
cs.IT math.IT
|
Recently, flash memories have become a competitive solution for mass storage.
The flash memories have rather different properties compared with the rotary
hard drives. That is, the writing of flash memories is constrained, and flash
memories can endure only limited numbers of erases. Therefore, the design goals
for the flash memory systems are quite different from these for other memory
systems. In this paper, we consider the problem of coding efficiency. We define
the "coding-efficiency" as the amount of information that one flash memory cell
can be used to record per cost. Because each flash memory cell can endure a
roughly fixed number of erases, the cost of data recording can be well-defined.
We define "payload" as the amount of information that one flash memory cell can
represent at a particular moment. By using information-theoretic arguments, we
prove a coding theorem for achievable coding rates. We prove an upper and lower
bound for coding efficiency. We show in this paper that there exists a
fundamental trade-off between "payload" and "coding efficiency". The results in
this paper may provide useful insights on the design of future flash memory
systems.
|
1202.0800
|
Error Resilience in Distributed Storage via Rank-Metric Codes
|
cs.IT math.IT
|
This paper presents a novel coding scheme for distributed storage systems
containing nodes with adversarial errors. The key challenge in such systems is
the propagation of erroneous data from a single corrupted node to the rest of
the system during a node repair process. This paper presents a concatenated
coding scheme which is based on two types of codes: maximum rank distance (MRD)
code as an outer code and optimal repair maximal distance separable (MDS) array
code as an inner code. Given this, two different types of adversarial errors
are considered: the first type considers an adversary that can replace the
content of an affected node only once; while the second attack-type considers
an adversary that can pollute data an unbounded number of times. This paper
proves that the proposed coding scheme attains a suitable upper bound on
resilience capacity for the first type of error. Further, the paper presents
mechanisms that combine this code with subspace signatures to achieve error
resilience for the second type of errors. Finally, the paper concludes by
presenting a construction based on MRD codes for optimal locally repairable
scalar codes that can tolerate adversarial errors.
|
1202.0813
|
On The Performance of Random Block Codes over Finite-State Fading
Channels
|
cs.IT math.IT
|
As the mobile application landscape expands, wireless networks are tasked
with supporting various connection profiles, including real-time communications
and delay-sensitive traffic. Among many ensuing engineering challenges is the
need to better understand the fundamental limits of forward error correction in
non-asymptotic regimes. This article seeks to characterize the performance of
block codes over finite-state channels with memory. In particular, classical
results from information theory are revisited in the context of channels with
rate transitions, and bounds on the probabilities of decoding failure are
derived for random codes. This study offers new insights about the potential
impact of channel correlation over time on overall performance.
|
1202.0835
|
Reducibility of joint relay positioning and flow optimization problem
|
cs.IT math.IT
|
This paper shows how to reduce the otherwise hard joint relay positioning and
flow optimization problem into a sequence a two simpler decoupled problems. We
consider a class of wireless multicast hypergraphs mainly characterized by
their hyperarc rate functions, that are increasing and convex in power, and
decreasing in distance between the transmit node and the farthest end node of
the hyperarc. The set-up consists of a single multicast flow session involving
a source, multiple destinations and a relay that can be positioned freely. The
first problem formulates the relay positioning problem in a purely geometric
sense, and once the optimal relay position is obtained the second problem
addresses the flow optimization. Furthermore, we present simple and efficient
algorithms to solve these problems.
|
1202.0837
|
On the influence of intelligence in (social) intelligence testing
environments
|
cs.AI
|
This paper analyses the influence of including agents of different degrees of
intelligence in a multiagent system. The goal is to better understand how we
can develop intelligence tests that can evaluate social intelligence. We
analyse several reinforcement algorithms in several contexts of cooperation and
competition. Our experimental setting is inspired by the recently developed
Darwin-Wallace distribution.
|
1202.0840
|
Lossy Compression via Sparse Linear Regression: Performance under
Minimum-distance Encoding
|
cs.IT math.IT stat.ML
|
We study a new class of codes for lossy compression with the squared-error
distortion criterion, designed using the statistical framework of
high-dimensional linear regression. Codewords are linear combinations of
subsets of columns of a design matrix. Called a Sparse Superposition or Sparse
Regression codebook, this structure is motivated by an analogous construction
proposed recently by Barron and Joseph for communication over an AWGN channel.
For i.i.d Gaussian sources and minimum-distance encoding, we show that such a
code can attain the Shannon rate-distortion function with the optimal error
exponent, for all distortions below a specified value. It is also shown that
sparse regression codes are robust in the following sense: a codebook designed
to compress an i.i.d Gaussian source of variance $\sigma^2$ with
(squared-error) distortion $D$ can compress any ergodic source of variance less
than $\sigma^2$ to within distortion $D$. Thus the sparse regression ensemble
retains many of the good covering properties of the i.i.d random Gaussian
ensemble, while having having a compact representation in terms of a matrix
whose size is a low-order polynomial in the block-length.
|
1202.0854
|
Reverse Compute and Forward: A Low-Complexity Architecture for Downlink
Distributed Antenna Systems
|
cs.IT math.IT
|
We consider a distributed antenna system where $L$ antenna terminals (ATs)
are connected to a Central Processor (CP) via digital error-free links of
finite capacity $R_0$, and serve $L$ user terminals (UTs). This system model
has been widely investigated both for the uplink and the downlink, which are
instances of the general multiple-access relay and broadcast relay networks. In
this work we focus on the downlink, and propose a novel downlink precoding
scheme nicknamed "Reverse Quantized Compute and Forward" (RQCoF). For this
scheme we obtain achievable rates and compare with the state of the art
available in the literature. We also provide simulation results for a realistic
network with fading and pathloss with $K > L$ UTs, and show that channel-based
user selection produces large benefits and essentially removes the problem of
rank deficiency in the system matrix.
|
1202.0855
|
A Reconstruction Error Formulation for Semi-Supervised Multi-task and
Multi-view Learning
|
cs.LG stat.ML
|
A significant challenge to make learning techniques more suitable for general
purpose use is to move beyond i) complete supervision, ii) low dimensional
data, iii) a single task and single view per instance. Solving these challenges
allows working with "Big Data" problems that are typically high dimensional
with multiple (but possibly incomplete) labelings and views. While other work
has addressed each of these problems separately, in this paper we show how to
address them together, namely semi-supervised dimension reduction for
multi-task and multi-view learning (SSDR-MML), which performs optimization for
dimension reduction and label inference in semi-supervised setting. The
proposed framework is designed to handle both multi-task and multi-view
learning settings, and can be easily adapted to many useful applications.
Information obtained from all tasks and views is combined via reconstruction
errors in a linear fashion that can be efficiently solved using an alternating
optimization scheme. Our formulation has a number of advantages. We explicitly
model the information combining mechanism as a data structure (a
weight/nearest-neighbor matrix) which allows investigating fundamental
questions in multi-task and multi-view learning. We address one such question
by presenting a general measure to quantify the success of simultaneous
learning of multiple tasks or from multiple views. We show that our SSDR-MML
approach can outperform many state-of-the-art baseline methods and demonstrate
the effectiveness of connecting dimension reduction and learning.
|
1202.0859
|
Imperfect Secrecy in Wiretap Channel II
|
cs.IT cs.CR math.IT
|
In a point-to-point communication system which consists of a sender, a
receiver and a set of noiseless channels, the sender wishes to transmit a
private message to the receiver through the channels which may be eavesdropped
by a wiretapper. The set of wiretap sets is arbitrary. The wiretapper can
access any one but not more than one wiretap set. From each wiretap set, the
wiretapper can obtain some partial information about the private message which
is measured by the equivocation of the message given the symbols obtained by
the wiretapper. The security strategy is to encode the message with some random
key at the sender. Only the message is required to be recovered at the
receiver. Under this setting, we define an achievable rate tuple consisting of
the size of the message, the size of the key, and the equivocation for each
wiretap set. We first prove a tight rate region when both the message and the
key are required to be recovered at the receiver. Then we extend the result to
the general case when only the message is required to be recovered at the
receiver. Moreover, we show that even if stochastic encoding is employed at the
sender, the message rate cannot be increased.
|
1202.0862
|
e-Valuate: A Two-player Game on Arithmetic Expressions -- An Update
|
math.CO cs.AI
|
e-Valuate is a game on arithmetic expressions. The players have contrasting
roles of maximizing and minimizing the given expression. The maximizer proposes
values and the minimizer substitutes them for variables of his choice. When the
expression is fully instantiated, its value is compared with a certain minimax
value that would result if the players played to their optimal strategies. The
winner is declared based on this comparison.
We use a game tree to represent the state of the game and show how the
minimax value can be computed efficiently using backward induction and
alpha-beta pruning. The efficacy of alpha-beta pruning depends on the order in
which the nodes are evaluated. Further improvements can be obtained by using
transposition tables to prevent reevaluation of the same nodes. We propose a
heuristic for node ordering. We show how the use of the heuristic and
transposition tables lead to improved performance by comparing the number of
nodes pruned by each method.
We describe some domain-specific variants of this game. The first is a graph
theoretic formulation wherein two players share a set of elements of a graph by
coloring a related set with each player looking to maximize his share. The set
being shared could be either the set of vertices, edges or faces (for a planar
graph). An application of this is the sharing of regions enclosed by a planar
graph where each player's aim is to maximize the area of his share. Another
variant is a tiling game where the players alternately place dominoes on a $8
\times 8$ checkerboard to construct a maximal partial tiling. We show that the
size of the tiling $x$ satisfies $22 \le x \le 32$ by proving that any maximal
partial tiling requires at least $22$ dominoes.
|
1202.0863
|
Asymptotically Good Codes Over Non-Abelian Groups
|
cs.IT math.IT
|
It has been shown that good structured codes over non-Abelian groups do
exist. Specifically, we construct codes over the smallest non-Abelian group
$\mathds{D}_6$ and show that the performance of these codes is superior to the
performance of Abelian group codes of the same alphabet size. This promises the
possibility of using non-Abelian codes for multi-terminal settings where the
structure of the code can be exploited to gain performance.
|
1202.0864
|
Nested Lattice Codes for Arbitrary Continuous Sources and Channels
|
cs.IT math.IT
|
In this paper, we show that nested lattice codes achieve the capacity of
arbitrary channels with or without non-casual state information at the
transmitter. We also show that nested lattice codes are optimal for source
coding with or without non-causal side information at the receiver for
arbitrary continuous sources.
|
1202.0865
|
A Compression Algorithm Using Mis-aligned Side-information
|
cs.IT math.IT
|
We study the problem of compressing a source sequence in the presence of
side-information that is related to the source via insertions, deletions and
substitutions. We propose a simple algorithm to compress the source sequence
when the side-information is present at both the encoder and decoder. A key
attribute of the algorithm is that it encodes the edits contained in runs of
different extents separately. For small insertion and deletion probabilities,
the compression rate of the algorithm is shown to be asymptotically optimal.
|
1202.0866
|
List-decoding of Subspace Codes and Rank-Metric Codes up to Singleton
Bound
|
cs.IT math.IT
|
Subspace codes and rank-metric codes can be used to correct errors and
erasures in network, with linear network coding. Subspace codes were introduced
by Koetter and Kschischang to correct errors and erasures in networks where
topology is unknown (the noncoherent case). In a previous work, we have
developed a family of subspace codes, based upon the Koetter-Kschichang
construction, which are efficiently list decodable. Using these codes, we
achieved a better decoding radius than Koetter-Kschischiang codes at low rates.
Herein, we introduce a new family of subspace codes based upon a different
approach which leads to a linear-algebraic list-decoding algorithm. The
resulting error correction radius can be expressed as follows: for any integer
$s$, our list-decoder using $s+1$-interpolation polynomials guarantees
successful recovery of the message subspace provided the normalized dimension
of errors is at most $s(1-sR)$. The same list-decoding algorithm can be used to
correct erasures as well as errors. The size of output list is at most
$Q^{s-1}$, where $Q$ is the size of the field that message symbols are chosen
from. Rank-metric codes are suitable for error correction in the case where the
network topology and the underlying network code are known (the coherent case).
Gabidulin codes are a well-known class of algebraic rank-metric codes that meet
the Singleton bound on the minimum rank metric of a code. In this paper, we
introduce a folded version of Gabidulin codes analogous to the folded
Reed-Solomon codes of Guruswami and Rudra along with a list-decoding algorithm
for such codes. Our list-decoding algorithm makes it possible to recover the
message provided that the normalized rank of error is at most $1-R-\epsilon$,
for any $\epsilon > 0$. Notably this achieves the information theoretic bound
on the decoding radius of a rank-metric code.
|
1202.0871
|
Channel Capacity under General Nonuniform Sampling
|
cs.IT math.IT
|
This paper develops the fundamental capacity limits of a sampled analog
channel under a sub-Nyquist sampling rate constraint. In particular, we derive
the capacity of sampled analog channels over a general class of time-preserving
sampling methods including irregular nonuniform sampling. Our results indicate
that the optimal sampling structures extract out the set of frequencies that
exhibits the highest SNR among all spectral sets of support size equal to the
sampling rate. The capacity under sub-Nyquist sampling can be attained through
filter-bank sampling, or through a single branch of modulation and filtering
followed by uniform sampling. The capacity under sub-Nyquist sampling is a
monotone function of the sampling rate. These results indicate that the optimal
sampling schemes suppress aliasing, and that employing irregular nonuniform
sampling does not provide capacity gain over uniform sampling sets with
appropriate preprocessing for a large class of channels.
|
1202.0876
|
A Coding Theoretic Approach for Evaluating Accumulate Distribution on
Minimum Cut Capacity of Weighted Random Graphs
|
cs.IT math.IT
|
The multicast capacity of a directed network is closely related to the
$s$-$t$ maximum flow, which is equal to the $s$-$t$ minimum cut capacity due to
the max-flow min-cut theorem. If the topology of a network (or link capacities)
is dynamically changing or have stochastic nature, it is not so trivial to
predict statistical properties on the maximum flow. In this paper, we present a
coding theoretic approach for evaluating the accumulate distribution of the
minimum cut capacity of weighted random graphs. The main feature of our
approach is to utilize the correspondence between the cut space of a graph and
a binary LDGM (low-density generator-matrix) code with column weight 2. The
graph ensemble treated in the paper is a weighted version of
Erd\H{o}s-R\'{e}nyi random graph ensemble. The main contribution of our work is
a combinatorial lower bound for the accumulate distribution of the minimum cut
capacity. From some computer experiments, it is observed that the lower bound
derived here reflects the actual statistical behavior of the minimum cut
capacity.
|
1202.0895
|
Causal Rate Distortion Function on Abstract Alphabets: Optimal
Reconstruction and Properties
|
cs.IT math.FA math.IT math.PR
|
A causal rate distortion function with a general fidelity criterion is
formulated on abstract alphabets and a coding theorem is derived. Existence of
the minimizing kernel is shown using the topology of weak convergence of
probability measures. The optimal reconstruction kernel is derived, which is
causal, and certain properties of the causal rate distortion function are
presented.
|
1202.0898
|
On Marton's inner bound for broadcast channels
|
cs.IT math.IT
|
Marton's inner bound is the best known achievable region for a general
discrete memoryless broadcast channel. To compute Marton's inner bound one has
to solve an optimization problem over a set of joint distributions on the input
and auxiliary random variables. The optimizers turn out to be structured in
many cases. Finding properties of optimizers not only results in efficient
evaluation of the region, but it may also help one to prove factorization of
Marton's inner bound (and thus its optimality). The first part of this paper
formulates this factorization approach explicitly and states some conjectures
and results along this line. The second part of this paper focuses primarily on
the structure of the optimizers. This section is inspired by a new binary
inequality that recently resulted in a very simple characterization of the
sum-rate of Marton's inner bound for binary input broadcast channels. This
prompted us to investigate whether this inequality can be extended to larger
cardinality input alphabets. We show that several of the results for the binary
input case do carry over for higher cardinality alphabets and we present a
collection of results that help restrict the search space of probability
distributions to evaluate the boundary of Marton's inner bound in the general
case. We also prove a new inequality for the binary skew-symmetric broadcast
channel that yields a very simple characterization of the entire Marton inner
bound for this channel.
|
1202.0914
|
Type-elimination-based reasoning for the description logic SHIQbs using
decision diagrams and disjunctive datalog
|
cs.LO cs.AI math.LO
|
We propose a novel, type-elimination-based method for reasoning in the
description logic SHIQbs including DL-safe rules. To this end, we first
establish a knowledge compilation method converting the terminological part of
an ALCIb knowledge base into an ordered binary decision diagram (OBDD) which
represents a canonical model. This OBDD can in turn be transformed into
disjunctive Datalog and merged with the assertional part of the knowledge base
in order to perform combined reasoning. In order to leverage our technique for
full SHIQbs, we provide a stepwise reduction from SHIQbs to ALCIb that
preserves satisfiability and entailment of positive and negative ground facts.
The proposed technique is shown to be worst case optimal w.r.t. combined and
data complexity and easily admits extensions with ground conjunctive queries.
|
1202.0919
|
Coordinating Complementary Waveforms for Sidelobe Suppression
|
cs.IT math.IT
|
We present a general method for constructing radar transmit pulse trains and
receive filters for which the radar point-spread function in delay and Doppler,
given by the cross-ambiguity function of the transmit pulse train and the pulse
train used in the receive filter, is essentially free of range sidelobes inside
a Doppler interval around the zero-Doppler axis. The transmit pulse train is
constructed by coordinating the transmission of a pair of Golay complementary
waveforms across time according to zeros and ones in a binary sequence P. The
pulse train used to filter the received signal is constructed in a similar way,
in terms of sequencing the Golay waveforms, but each waveform in the pulse
train is weighted by an element from another sequence Q. We show that a
spectrum jointly determined by P and Q sequences controls the size of the range
sidelobes of the cross-ambiguity function and by properly choosing P and Q we
can clear out the range sidelobes inside a Doppler interval around the zero-
Doppler axis. The joint design of P and Q enables a tradeoff between the order
of the spectral null for range sidelobe suppression and the signal-to-noise
ratio at the receiver output. We establish this trade-off and derive a
necessary and sufficient condition for the construction of P and Q sequences
that produce a null of a desired order.
|
1202.0922
|
Low-distortion Inference of Latent Similarities from a Multiplex Social
Network
|
cs.SI cs.DS physics.soc-ph
|
Much of social network analysis is - implicitly or explicitly - predicated on
the assumption that individuals tend to be more similar to their friends than
to strangers. Thus, an observed social network provides a noisy signal about
the latent underlying "social space:" the way in which individuals are similar
or dissimilar. Many research questions frequently addressed via social network
analysis are in reality questions about this social space, raising the question
of inverting the process: Given a social network, how accurately can we
reconstruct the social structure of similarities and dissimilarities?
We begin to address this problem formally. Observed social networks are
usually multiplex, in the sense that they reflect (dis)similarities in several
different "categories," such as geographical proximity, kinship, or similarity
of professions/hobbies. We assume that each such category is characterized by a
latent metric capturing (dis)similarities in this category. Each category gives
rise to a separate social network: a random graph parameterized by this metric.
For a concrete model, we consider Kleinberg's small world model and some
variations thereof. The observed social network is the unlabeled union of these
graphs, i.e., the presence or absence of edges can be observed, but not their
origins. Our main result is an algorithm which reconstructs each metric with
provably low distortion.
|
1202.0925
|
Alternating Markov Chains for Distribution Estimation in the Presence of
Errors
|
cs.IT math.IT
|
We consider a class of small-sample distribution estimators over noisy
channels. Our estimators are designed for repetition channels, and rely on
properties of the runs of the observed sequences. These runs are modeled via a
special type of Markov chains, termed alternating Markov chains. We show that
alternating chains have redundancy that scales sub-linearly with the lengths of
the sequences, and describe how to use a distribution estimator for alternating
chains for the purpose of distribution estimation over repetition channels.
|
1202.0932
|
Error-Correction in Flash Memories via Codes in the Ulam Metric
|
cs.IT math.IT
|
We consider rank modulation codes for flash memories that allow for handling
arbitrary charge-drop errors. Unlike classical rank modulation codes used for
correcting errors that manifest themselves as swaps of two adjacently ranked
elements, the proposed \emph{translocation rank codes} account for more general
forms of errors that arise in storage systems. Translocations represent a
natural extension of the notion of adjacent transpositions and as such may be
analyzed using related concepts in combinatorics and rank modulation coding.
Our results include derivation of the asymptotic capacity of translocation rank
codes, construction techniques for asymptotically good codes, as well as simple
decoding methods for one class of constructed codes. As part of our exposition,
we also highlight the close connections between the new code family and
permutations with short common subsequences, deletion and insertion
error-correcting codes for permutations, and permutation codes in the Hamming
distance.
|
1202.0934
|
Action Dependent Strictly Causal State Communication
|
cs.IT math.IT
|
The problem of communication and state estimation is considered in the
context of channels with actiondependent states. Given the message to be
communicated, the transmitter chooses an action sequence that affects the
formation of the channel states, and then creates the channel input sequence
based on the state sequence. The decoder estimates the channel to some
distortion as well as decodes the message. The capacity-distortion tradeoff of
such a channel is characterized for the case when the state information is
available strictly causally at the channel encoder. The problem setting extends
the action dependent framework of [1] and as a special case recovers the
results of few previously considered joint communication and estimation
scenarios in [2], [3], [4]. The scenario when the action is also allowed to
depend on the past observed states (adaptive action) is also considered. It is
shown that such adaptive action yields an improved capacity-distortion
function.
|
1202.0936
|
Dithered quantizers with negligible in-band dither power
|
cs.IT math.IT
|
Subtractive dithered quantizers are examined to minimize the signal-band
dither power. The design of finite impulse response(FIR) filters that shape
most of the dither-power out of the signal band while maintaining the benefits
of dithering are dealt with in detail. Simulation results for low-medium
resolution quantizers are presented to highlight the overall design
consideration.
|
1202.0937
|
Compressive binary search
|
cs.IT math.IT
|
In this paper we consider the problem of locating a nonzero entry in a
high-dimensional vector from possibly adaptive linear measurements. We consider
a recursive bisection method which we dub the compressive binary search and
show that it improves on what any nonadaptive method can achieve. We also
establish a non-asymptotic lower bound that applies to all methods, regardless
of their computational complexity. Combined, these results show that the
compressive binary search is within a double logarithmic factor of the optimal
performance.
|
1202.0940
|
Improving feature selection algorithms using normalised feature
histograms
|
cs.AI cs.CV
|
The proposed feature selection method builds a histogram of the most stable
features from random subsets of a training set and ranks the features based on
a classifier based cross-validation. This approach reduces the instability of
features obtained by conventional feature selection methods that occur with
variation in training data and selection criteria. Classification results on
four microarray and three image datasets using three major feature selection
criteria and a naive Bayes classifier show considerable improvement over
benchmark results.
|
1202.0946
|
Gaussian Stochastic Linearization for Open Quantum Systems Using
Quadratic Approximation of Hamiltonians
|
quant-ph cs.SY math.OC math.PR
|
This paper extends the energy-based version of the stochastic linearization
method, known for classical nonlinear systems, to open quantum systems with
canonically commuting dynamic variables governed by quantum stochastic
differential equations with non-quadratic Hamiltonians. The linearization
proceeds by approximating the actual Hamiltonian of the quantum system by a
quadratic function of its observables which corresponds to the Hamiltonian of a
quantum harmonic oscillator. This approximation is carried out in a mean square
optimal sense with respect to a Gaussian reference quantum state and leads to a
self-consistent linearization procedure where the mean vector and quantum
covariance matrix of the system observables evolve in time according to the
effective linear dynamics. We demonstrate the proposed Hamiltonian-based
Gaussian linearization for the quantum Duffing oscillator whose Hamiltonian is
a quadro-quartic polynomial of the momentum and position operators. The results
of the paper are applicable to the design of suboptimal controllers and filters
for nonlinear quantum systems.
|
1202.0958
|
Directed Information on Abstract spaces: Properties and Extremum
Problems
|
cs.IT math.FA math.IT math.PR
|
This paper describes a framework in which directed information is defined on
abstract spaces. The framework is employed to derive properties of directed
information such as convexity, concavity, lower semicontinuity, by using the
topology of weak convergence of probability measures on Polish spaces. Two
extremum problems of directed information related to capacity of channels with
memory and feedback, and non-anticipative and sequential rate distortion are
analyzed showing existence of maximizing and minimizing distributions,
respectively.
|
1202.0959
|
A New Random Coding Technique that Generalizes Superposition Coding and
Binning
|
cs.IT math.IT
|
Proving capacity for networks without feedback or cooperation usually
involves two fundamental random coding techniques: superposition coding and
binning. Although conceptually very different, these two techniques often
achieve the same performance, suggesting an underlying similarity. In this
correspondence we propose a new random coding technique that generalizes
superposition coding and binning and provides new insight on relationship among
the two With this new theoretical tool, we derive new achievable regions for
three classical information theoretical models: multi-access channel, broadcast
channel, the interference channel, and show that, unfortunately, it does not
improve over the largest known achievable regions for these cases.
|
1202.0961
|
On the Capacity of a General Multiple-Access Channel and of a Cognitive
Network in the Very Strong Interference Regime
|
cs.IT math.IT
|
The capacity of the multiple-access channel with any distribution of messages
among the transmitting nodes was determined by Han in 1979 and the expression
of the capacity region contains a number of rate bounds and that grows
exponentially with the number of messages. We derive a more compact expression
for the capacity region of this channel in which the number of rate bounds
depends on the distribution of the messages at the encoders. Using this
expression we prove capacity for a class of general cognitive network that we
denote as "very strong interference" regime. In this regime there is no rate
loss in having all the receivers decode all the messages and the capacity
region reduces to the capacity of the compound multiple-access channel. This
result generalizes the "very strong interference" capacity results for the
interference channel, the cognitive interference channel, the interference
channel with a cognitive relay and many others.
|
1202.0977
|
The Capacity of the Semi-Deterministic Cognitive Interference Channel
with a Common Cognitive Message and Approximate Capacity for the Gaussian
Case
|
cs.IT math.IT
|
In this paper the study of the cognitive interference channel with a common
message, a variation of the classical cognitive interference channel in which
the cognitive message is decoded at both receivers. We derive the capacity for
the semideterministic channel in which the output at the cognitive decoder is a
deterministic function of the channel inputs. We also show capacity to within a
constant gap and a constant factor for the Gaussian channel in which the
outputs are linear combinations of the channel inputs plus an additive Gaussian
noise term. Most of these results are shown using an interesting transmission
scheme in which the cognitive message, decoded at both receivers, is also
pre-coded against the interference experienced at the cognitive decoder. The
pre-coding of the cognitive message does not allow the primary decoder to
reconstruct the interfering signal. The cognitive message acts instead as a
side information at the primary receiver when decoding its intended message.
|
1202.0979
|
Spatially-Coupled Binary MacKay-Neal Codes for Channels with Non-Binary
Inputs and Affine Subspace Outputs
|
cs.IT math.IT
|
We study LDPC codes for the channel with $2^m$-ary input $\underline{x}\in
\mathbb{F}_2^m$ and output $\underline{y}=\underline{x}+\underline{z}\in
\mathbb{F}_2^m$. The receiver knows a subspace $V\subset \mathbb{F}_2^m$ from
which $\underline{z}=\underline{y}-\underline{x}$ is uniformly chosen. Or
equivalently, the receiver receives an affine subspace $\underline{y}-V$ where
$\underline{x}$ lies. We consider a joint iterative decoder involving the
channel detector and the LDPC decoder. The decoding system considered in this
paper can be viewed as a simplified model of the joint iterative decoder over
non-binary modulated signal inputs e.g., $2^m$-QAM. We evaluate the performance
of binary spatially-coupled MacKay-Neal codes by density evolution. The
iterative decoding threshold is seriously degraded by increasing $m$. EXIT-like
function curve calculations reveal that this degradation is caused by wiggles
and can be mitigated by increasing the randomized window size. The resultant
iterative decoding threshold values are very close to the Shannon limit.
|
1202.0984
|
OWL: Yet to arrive on the Web of Data?
|
cs.DL cs.AI
|
Seven years on from OWL becoming a W3C recommendation, and two years on from
the more recent OWL 2 W3C recommendation, OWL has still experienced only patchy
uptake on the Web. Although certain OWL features (like owl:sameAs) are very
popular, other features of OWL are largely neglected by publishers in the
Linked Data world. This may suggest that despite the promise of easy
implementations and the proposal of tractable profiles suggested in OWL's
second version, there is still no "right" standard fragment for the Linked Data
community. In this paper, we (1) analyse uptake of OWL on the Web of Data, (2)
gain insights into the OWL fragment that is actually used/usable on the Web,
where we arrive at the conclusion that this fragment is likely to be a
simplified profile based on OWL RL, (3) propose and discuss such a new
fragment, which we call OWL LD (for Linked Data).
|
1202.0992
|
Computational Results of Duadic Double Circulant Codes
|
cs.IT cs.DM math.CO math.IT
|
Quadratic residue codes have been one of the most important classes of
algebraic codes. They have been generalized into duadic codes and quadratic
double circulant codes. In this paper we introduce a new subclass of double
circulant codes, called {\em{duadic double circulant codes}}, which is a
generalization of quadratic double circulant codes for prime lengths. This
class generates optimal self-dual codes, optimal linear codes, and linear codes
with the best known parameters in a systematic way. We describe a method to
construct duadic double circulant codes using 4-cyclotomic cosets and give
certain duadic double circulant codes over $\mathbb F_2, \mathbb F_3, \mathbb
F_4, \mathbb F_5$, and $\mathbb F_7$. In particular, we find a new ternary
self-dual $[76,38,18]$ code and easily rediscover optimal binary self-dual
codes with parameters $[66,33,12]$, $[68,34,12]$, $[86,43,16]$, and
$[88,44,16]$ as well as a formally self-dual binary $[82,41,14]$ code.
|
1202.1050
|
Regenerating Codes for Errors and Erasures in Distributed Storage
|
cs.IT cs.DC cs.NI math.IT
|
Regenerating codes are a class of codes proposed for providing reliability of
data and efficient repair of failed nodes in distributed storage systems. In
this paper, we address the fundamental problem of handling errors and erasures
during the data-reconstruction and node-repair operations. We provide explicit
regenerating codes that are resilient to errors and erasures, and show that
these codes are optimal with respect to storage and bandwidth requirements. As
a special case, we also establish the capacity of a class of distributed
storage systems in the presence of malicious adversaries. While our code
constructions are based on previously constructed Product-Matrix codes, we also
provide necessary and sufficient conditions for introducing resilience in any
regenerating code.
|
1202.1054
|
Considering a resource-light approach to learning verb valencies
|
cs.CL
|
Here we describe work on learning the subcategories of verbs in a
morphologically rich language using only minimal linguistic resources. Our goal
is to learn verb subcategorizations for Quechua, an under-resourced
morphologically rich language, from an unannotated corpus. We compare results
from applying this approach to an unannotated Arabic corpus with those achieved
by processing the same text in treebank form. The original plan was to use only
a morphological analyzer and an unannotated corpus, but experiments suggest
that this approach by itself will not be effective for learning the
combinatorial potential of Arabic verbs in general. The lower bound on
resources for acquiring this information is somewhat higher, apparently
requiring a a part-of-speech tagger and chunker for most languages, and a
morphological disambiguater for Arabic.
|
1202.1060
|
A Non-Disjoint Group Shuffled Decoding for LDPC Codes
|
cs.IT math.IT
|
To reduce the implementation complexity of a belief propagation (BP) based
low-density parity-check (LDPC) decoder, shuffled BP decoding schedules, which
serialize the decoding process by dividing a complete parallel message-passing
iteration into a sequence of sub-iterations, have been proposed. The so-called
group horizontal shuffled BP algorithm partitions the check nodes of the code
graph into groups to perform group-by-group message-passing decoding. This
paper proposes a new grouping technique to accelerate the message-passing rate.
Performance of the proposed algorithm is analyzed by a Gaussian approximation
approach. Both analysis and numerical experiments verify that the new algorithm
does yield a convergence rate faster than that of existing conventional or
group shuffled BP decoder with the same computing complexity constraint.
|
1202.1081
|
Some Comments on the Strong Simplex Conjecture
|
cs.IT math.IT
|
In the disproof of the Strong Simplex Conjecture presented in [Steiner,
1994], a counterexample signal set was found that has higher average
probability of correct optimal decoding than the corresponding regular simplex
signal set, when compared at small values of the signal-to-noise ratio. The
latter was defined as the quotient of average signal energy and average noise
power. In this paper, it is shown that this interpretation of the
signal-to-noise ratio is inappropriate for a comparison of signal sets, since
it leads to a contradiction with the Channel Coding Theorem. A modified
counterexample signal set is proposed and examined using the classical
interpretation of the signal-to-noise ratio, i.e., as the quotient of average
signal energy and average noise energy. This signal set outperforms the regular
simplex signal set for small signal-to-noise ratios without contradicting the
Channel Coding Theorem, hence the Strong Simplex Conjecture remains proven
false.
|
1202.1100
|
Wavelets for Single Carrier Communications
|
cs.NI cs.IT math.IT
|
This paper and the following presentation aim to provide a report regarding
the seminar presentation given on 23.02.2011 as a part of the postgraduate
seminar course S-88.4223 Wavelets in Communications lectured by Dr. Sumesh
Parameswaran at Aalto University School of Electrical Engineering. In
particular, the topic on "wavelets for single carrier communications" has been
considered herein. Furthermore, a summary of wavelets in Single Carrier
(SC)-FDMA Systems is as well provided.
|
1202.1112
|
Recommender Systems
|
physics.soc-ph cond-mat.stat-mech cs.IR cs.SI
|
The ongoing rapid expansion of the Internet greatly increases the necessity
of effective recommender systems for filtering the abundant information.
Extensive research for recommender systems is conducted by a broad range of
communities including social and computer scientists, physicists, and
interdisciplinary researchers. Despite substantial theoretical and practical
achievements, unification and comparison of different approaches are lacking,
which impedes further advances. In this article, we review recent developments
in recommender systems and discuss the major challenges. We compare and
evaluate available algorithms and examine their roles in the future
developments. In addition to algorithms, physical aspects are described to
illustrate macroscopic behavior of recommender systems. Potential impacts and
future directions are discussed. We emphasize that recommendation has a great
scientific depth and combines diverse research fields which makes it of
interests for physicists as well as interdisciplinary researchers.
|
1202.1119
|
Cramer Rao-Type Bounds for Sparse Bayesian Learning
|
cs.LG stat.ML
|
In this paper, we derive Hybrid, Bayesian and Marginalized Cram\'{e}r-Rao
lower bounds (HCRB, BCRB and MCRB) for the single and multiple measurement
vector Sparse Bayesian Learning (SBL) problem of estimating compressible
vectors and their prior distribution parameters. We assume the unknown vector
to be drawn from a compressible Student-t prior distribution. We derive CRBs
that encompass the deterministic or random nature of the unknown parameters of
the prior distribution and the regression noise variance. We extend the MCRB to
the case where the compressible vector is distributed according to a general
compressible prior distribution, of which the generalized Pareto distribution
is a special case. We use the derived bounds to uncover the relationship
between the compressibility and Mean Square Error (MSE) in the estimates.
Further, we illustrate the tightness and utility of the bounds through
simulations, by comparing them with the MSE performance of two popular
SBL-based estimators. It is found that the MCRB is generally the tightest among
the bounds derived and that the MSE performance of the Expectation-Maximization
(EM) algorithm coincides with the MCRB for the compressible vector. Through
simulations, we demonstrate the dependence of the MSE performance of SBL based
estimators on the compressibility of the vector for several values of the
number of observations and at different signal powers.
|
1202.1120
|
Optimum Power Allocations for Fading Decode-and-Forward Relay Channel
|
cs.IT math.IT
|
In this paper, for a fading decode-and-forward full-duplex relay channel, we
analytically derive optimum power allocations. Individual power constraints for
the source and the relay are assumed and the related optimization problem is
analyzed for two scenarios. First, optimization is taken over the source power,
the relay power, and the correlation coefficient between the transmitted
signals of the source and the relay. Then, for a fixed value of correlation
coefficient, the optimization problem is analyzed. It is also proven that the
optimization problems are convex for these two scenarios. Finally, implications
of theoretical results are discussed through simulations for each scenario.
|
1202.1121
|
rFerns: An Implementation of the Random Ferns Method for General-Purpose
Machine Learning
|
cs.LG stat.ML
|
In this paper I present an extended implementation of the Random ferns
algorithm contained in the R package rFerns. It differs from the original by
the ability of consuming categorical and numerical attributes instead of only
binary ones. Also, instead of using simple attribute subspace ensemble it
employs bagging and thus produce error approximation and variable importance
measure modelled after Random forest algorithm. I also present benchmarks'
results which show that although Random ferns' accuracy is mostly smaller than
achieved by Random forest, its speed and good quality of importance measure it
provides make rFerns a reasonable choice for a specific applications.
|
1202.1125
|
Information Divergence is more chi squared distributed than the chi
squared statistics
|
math.ST cs.IT math.IT stat.TH
|
For testing goodness of fit it is very popular to use either the chi square
statistic or G statistics (information divergence). Asymptotically both are chi
square distributed so an obvious question is which of the two statistics that
has a distribution that is closest to the chi square distribution.
Surprisingly, when there is only one degree of freedom it seems like the
distribution of information divergence is much better approximated by a chi
square distribution than the chi square statistic. For random variables we
introduce a new transformation that transform several important distributions
into new random variables that are almost Gaussian. For the binomial
distributions and the Poisson distributions we formulate a general conjecture
about how close their transform are to the Gaussian. The conjecture is proved
for Poisson distributions.
|
1202.1144
|
Achievable Angles Between two Compressed Sparse Vectors Under
Norm/Distance Constraints Imposed by the Restricted Isometry Property: A
Plane Geometry Approach
|
cs.IT math.IT
|
The angle between two compressed sparse vectors subject to the norm/distance
constraints imposed by the restricted isometry property (RIP) of the sensing
matrix plays a crucial role in the studies of many compressive sensing (CS)
problems. Assuming that (i) u and v are two sparse vectors separated by an
angle thetha, and (ii) the sensing matrix Phi satisfies RIP, this paper is
aimed at analytically characterizing the achievable angles between Phi*u and
Phi*v. Motivated by geometric interpretations of RIP and with the aid of the
well-known law of cosines, we propose a plane geometry based formulation for
the study of the considered problem. It is shown that all the RIP-induced
norm/distance constraints on Phi*u and Phi*v can be jointly depicted via a
simple geometric diagram in the two-dimensional plane. This allows for a joint
analysis of all the considered algebraic constraints from a geometric
perspective. By conducting plane geometry analyses based on the constructed
diagram, closed-form formulae for the maximal and minimal achievable angles are
derived. Computer simulations confirm that the proposed solution is tighter
than an existing algebraic-based estimate derived using the polarization
identity. The obtained results are used to derive a tighter restricted isometry
constant of structured sensing matrices of a certain kind, to wit, those in the
form of a product of an orthogonal projection matrix and a random sensing
matrix. Follow-up applications to three CS problems, namely, compressed-domain
interference cancellation, RIP-based analysis of the orthogonal matching
pursuit algorithm, and the study of democratic nature of random sensing
matrices are investigated.
|
1202.1145
|
Effects of time window size and placement on the structure of aggregated
networks
|
physics.soc-ph cs.SI
|
Complex networks are often constructed by aggregating empirical data over
time, such that a link represents the existence of interactions between the
endpoint nodes and the link weight represents the intensity of such
interactions within the aggregation time window. The resulting networks are
then often considered static. More often than not, the aggregation time window
is dictated by the availability of data, and the effects of its length on the
resulting networks are rarely considered. Here, we address this question by
studying the structural features of networks emerging from aggregating
empirical data over different time intervals, focussing on networks derived
from time-stamped, anonymized mobile telephone call records. Our results show
that short aggregation intervals yield networks where strong links associated
with dense clusters dominate; the seeds of such clusters or communities become
already visible for intervals of around one week. The degree and weight
distributions are seen to become stationary around a few days and a few weeks,
respectively. An aggregation interval of around 30 days results in the stablest
similar networks when consecutive windows are compared. For longer intervals,
the effects of weak or random links become increasingly stronger, and the
average degree of the network keeps growing even for intervals up to 180 days.
The placement of the time window is also seen to affect the outcome: for short
windows, different behavioural patterns play a role during weekends and
weekdays, and for longer windows it is seen that networks aggregated during
holiday periods are significantly different.
|
1202.1150
|
Optimal Index Codes with Near-Extreme Rates
|
cs.IT math.IT
|
The min-rank of a digraph was shown by Bar-Yossef et al. (2006) to represent
the length of an optimal scalar linear solution of the corresponding instance
of the Index Coding with Side Information (ICSI) problem. In this work, the
graphs and digraphs of near-extreme min-ranks are characterized. Those graphs
and digraphs correspond to the ICSI instances having near-extreme transmission
rates when using optimal scalar linear index codes. In particular, it is shown
that the decision problem whether a digraph has min-rank two is NP-complete. By
contrast, the same question for graphs can be answered in polynomial time.
Additionally, a new upper bound on the min-rank of a digraph, the
circuit-packing bound, is presented. This bound is often tighter than the
previously known bounds. By employing this new bound, we present several
families of digraphs whose min-ranks can be found in polynomial time.
|
1202.1174
|
Base station selection for energy efficient network operation with the
majorization-minimization algorithm
|
cs.IT math.IT
|
In this paper, we study the problem of reducing the energy consumption in a
mobile communication network; we select the smallest set of active base
stations that can preserve the quality of service (the minimum data rate)
required by the users. In more detail, we start by posing this problem as an
integer programming problem, the solution of which shows the optimal assignment
(in the sense of minimizing the total energy consumption) between base stations
and users. In particular, this solution shows which base stations can then be
switched off or put in idle mode to save energy. However, solving this problem
optimally is intractable in general, so in this study we develop a suboptimal
approach that builds upon recent techniques that have been successfully applied
to, among other problems, sparse signal reconstruction, portfolio optimization,
statistical estimation, and error correction. More precisely, we relax the
original integer programming problem as a minimization problem where the
objective function is concave and the constraint set is convex. The resulting
relaxed problem is still intractable in general, but we can apply the
majorization-minimization algorithm to find good solutions (i.e., solutions
attaining low objective value) with a low-complexity algorithm. In contrast to
state-of-the-art approaches, the proposed algorithm can take into account
inter-cell interference, is suitable for large-scale problems, and can be
applied to heterogeneous networks (networks where base station consume
different amounts of energy)
|
1202.1178
|
Wireless Network Control with Privacy Using Hybrid ARQ
|
cs.IT math.IT
|
We consider the problem of resource allocation in a wireless cellular
network, in which nodes have both open and private information to be
transmitted to the base station over block fading uplink channels. We develop a
cross-layer solution, based on hybrid ARQ transmission with incremental
redundancy. We provide a scheme that combines power control, flow control, and
scheduling in order to maximize a global utility function, subject to the
stability of the data queues, an average power constraint, and a constraint on
the privacy outage probability. Our scheme is based on the assumption that each
node has an estimate of its uplink channel gain at each block, while only the
distribution of the cross channel gains is available. We prove that our scheme
achieves a utility, arbitrarily close to the maximum achievable utility given
the available channel state information.
|
1202.1209
|
Wyner-Ziv Type Versus Noisy Network Coding For a State-Dependent MAC
|
cs.IT math.IT
|
We consider a two-user state-dependent multiaccess channel in which the
states of the channel are known non-causally to one of the encoders and only
strictly causally to the other encoder. Both encoders transmit a common message
and, in addition, the encoder that knows the states non-causally transmits an
individual message. We find explicit characterizations of the capacity region
of this communication model in both discrete memoryless and memoryless Gaussian
cases. The analysis also reveals optimal ways of exploiting the knowledge of
the state only strictly causally at the encoder that sends only the common
message when such a knowledge is beneficial. The encoders collaborate to convey
to the decoder a lossy version of the state, in addition to transmitting the
information messages through a generalized Gel'fand-Pinsker binning.
Particularly important in this problem are the questions of 1) optimal ways of
performing the state compression and 2) whether or not the compression indices
should be decoded uniquely. We show that both compression \`a-la noisy network
coding, i.e., with no binning, and compression using Wyner-Ziv binning are
optimal. The scheme that uses Wyner-Ziv binning shares elements with Cover and
El Gamal original compress-and-forward, but differs from it mainly in that
backward decoding is employed instead of forward decoding and the compression
indices are not decoded uniquely. Finally, by exploring the properties of our
outer bound, we show that, although not required in general, the compression
indices can in fact be decoded uniquely essentially without altering the
capacity region, but at the expense of larger alphabets sizes for the auxiliary
random variables.
|
1202.1212
|
Robust 1-bit compressed sensing and sparse logistic regression: A convex
programming approach
|
cs.IT math.IT math.ST stat.TH
|
This paper develops theoretical results regarding noisy 1-bit compressed
sensing and sparse binomial regression. We show that a single convex program
gives an accurate estimate of the signal, or coefficient vector, for both of
these models. We demonstrate that an s-sparse signal in R^n can be accurately
estimated from m = O(slog(n/s)) single-bit measurements using a simple convex
program. This remains true even if each measurement bit is flipped with
probability nearly 1/2. Worst-case (adversarial) noise can also be accounted
for, and uniform results that hold for all sparse inputs are derived as well.
In the terminology of sparse logistic regression, we show that O(slog(n/s))
Bernoulli trials are sufficient to estimate a coefficient vector in R^n which
is approximately s-sparse. Moreover, the same convex program works for
virtually all generalized linear models, in which the link function may be
unknown. To our knowledge, these are the first results that tie together the
theory of sparse logistic regression to 1-bit compressed sensing. Our results
apply to general signal structures aside from sparsity; one only needs to know
the size of the set K where signals reside. The size is given by the mean width
of K, a computable quantity whose square serves as a robust extension of the
dimension.
|
1202.1229
|
Key recycling in authentication
|
cs.IT cs.CR math.IT quant-ph
|
In their seminal work on authentication, Wegman and Carter propose that to
authenticate multiple messages, it is sufficient to reuse the same hash
function as long as each tag is encrypted with a one-time pad. They argue that
because the one-time pad is perfectly hiding, the hash function used remains
completely unknown to the adversary.
Since their proof is not composable, we revisit it using a composable
security framework. It turns out that the above argument is insufficient: if
the adversary learns whether a corrupted message was accepted or rejected,
information about the hash function is leaked, and after a bounded finite
amount of rounds it is completely known. We show however that this leak is very
small: Wegman and Carter's protocol is still $\epsilon$-secure, if
$\epsilon$-almost strongly universal$_2$ hash functions are used. This implies
that the secret key corresponding to the choice of hash function can be reused
in the next round of authentication without any additional error than this
$\epsilon$.
We also show that if the players have a mild form of synchronization, namely
that the receiver knows when a message should be received, the key can be
recycled for any arbitrary task, not only new rounds of authentication.
|
1202.1238
|
List decoding of repeated codes
|
cs.IT math.IT
|
Assuming that we have a soft-decision list decoding algorithm of a linear
code, a new hard-decision list decoding algorithm of its repeated code is
proposed in this article. Although repeated codes are not used for encoding
data, due to their parameters, we show that they have a good performance with
this algorithm. We compare, by computer simulations, our algorithm for the
repeated code of a Reed-Solomon code against a decoding algorithm of a
Reed-Solomon code. Finally, we estimate the decoding capability of the
algorithm for Reed-Solomon codes and show that performance is somewhat better
than our estimates.
|
1202.1254
|
Optimal Sum-Rate of the Vector Gaussian CEO Problem
|
cs.IT math.IT
|
This document is withdrawn due to an error in Lemma 4.
|
1202.1307
|
Robust Multi-Robot Optimal Path Planning with Temporal Logic Constraints
|
cs.RO
|
In this paper we present a method for automatically planning robust optimal
paths for a group of robots that satisfy a common high level mission
specification. Each robot's motion in the environment is modeled as a weighted
transition system, and the mission is given as a Linear Temporal Logic (LTL)
formula over a set of propositions satisfied by the regions of the environment.
In addition, an optimizing proposition must repeatedly be satisfied. The goal
is to minimize the maximum time between satisfying instances of the optimizing
proposition while ensuring that the LTL formula is satisfied even with
uncertainty in the robots' traveling times. We characterize a class of LTL
formulas that are robust to robot timing errors, for which we generate optimal
paths if no timing errors are present, and we present bounds on the deviation
from the optimal values in the presence of errors. We implement and
experimentally evaluate our method considering a persistent monitoring task in
a road network environment.
|
1202.1325
|
Mutual-Information Optimized Quantization for LDPC Decoding of
Accurately Modeled Flash Data
|
cs.IT math.IT
|
High-capacity NAND flash memories use multi-level cells (MLCs) to store
multiple bits per cell and achieve high storage densities. Higher densities
cause increased raw bit error rates (BERs), which demand powerful error
correcting codes. Low-density parity-check (LDPC) codes are a well-known class
of capacity-approaching codes in AWGN channels. However, LDPC codes
traditionally use soft information while the flash read channel provides only
hard information. Low resolution soft information may be obtained by performing
multiple reads per cell with distinct word-line voltages.
We select the values of these word-line voltages to maximize the mutual
information between the input and output of the equivalent multiple-read
channel under any specified noise model. Our results show that maximum
mutual-information (MMI) quantization provides better soft information for LDPC
decoding given the quantization level than the constant-pdf-ratio quantization
approach. We also show that adjusting the LDPC code degree distribution for the
quantized setting provides a significant performance improvement.
|
1202.1327
|
Asymptotically Optimal Algorithms for Pickup and Delivery Problems with
Application to Large-Scale Transportation Systems
|
cs.SY
|
The Stacker Crane Problem is NP-Hard and the best known approximation
algorithm only provides a 9/5 approximation ratio. The objective of this paper
is threefold. First, by embedding the problem within a stochastic framework, we
present a novel algorithm for the SCP that: (i) is asymptotically optimal,
i.e., it produces, almost surely, a solution approaching the optimal one as the
number of pickups/deliveries goes to infinity; and (ii) has computational
complexity $O(n^{2+\eps})$, where $n$ is the number of pickup/delivery pairs
and $\eps$ is an arbitrarily small positive constant. Second, we asymptotically
characterize the length of the optimal SCP tour. Finally, we study a dynamic
version of the SCP, whereby pickup and delivery requests arrive according to a
Poisson process, and which serves as a model for large-scale demand-responsive
transport (DRT) systems. For such a dynamic counterpart of the SCP, we derive a
necessary and sufficient condition for the existence of stable vehicle routing
policies, which depends only on the workspace geometry, the stochastic
distributions of pickup and delivery points, the arrival rate of requests, and
the number of vehicles. Our results leverage a novel connection between the
Euclidean Bipartite Matching Problem and the theory of random permutations,
and, for the dynamic setting, exhibit novel features that are absent in
traditional spatially-distributed queueing systems.
|
1202.1330
|
A dual modelling of evolving political opinion networks
|
physics.soc-ph cs.SI stat.CO
|
We present the result of a dual modeling of opinion network. The model
complements the agent-based opinion models by attaching to the social agent
(voters) network a political opinion (party) network having its own intrinsic
mechanisms of evolution. These two sub-networks form a global network which can
be either isolated from or dependent on the external influence. Basically, the
evolution of the agent network includes link adding and deleting, the opinion
changes influenced by social validation, the political climate, the
attractivity of the parties and the interaction between them. The opinion
network is initially composed of numerous nodes representing opinions or
parties which are located on a one dimensional axis according to their
political positions. The mechanism of evolution includes union, splitting,
change of position and of attractivity, taken into account the pairwise node
interaction decaying with node distance in power law. The global evolution ends
in a stable distribution of the social agents over a quasi-stable and
fluctuating stationary number of remaining parties. Empirical study on the
lifetime distribution of numerous parties and vote results is carried out to
verify numerical results.
|
1202.1332
|
Secure Multiplex Coding with Dependent and Non-Uniform Multiple Messages
|
cs.IT cs.CR math.IT
|
The secure multiplex coding (SMC) is a technique to remove rate loss in the
coding for wire-tap channels and broadcast channels with confidential messages
caused by the inclusion of random bits into transmitted signals. SMC replaces
the random bits by other meaningful secret messages, and a collection of secret
messages serves as the random bits to hide the rest of messages. In the
previous researches, multiple secret messages were assumed to have independent
and uniform distributions, which is difficult to be ensured in practice. We
remove this restrictive assumption by a generalization of the channel
resolvability technique.
We also give practical construction techniques for SMC by using an arbitrary
given error-correcting code as an ingredient, and channel-universal coding of
SMC. By using the same principle as the channel-universal SMC, we give coding
for the broadcast channel with confidential messages universal to both channel
and source distributions.
|
1202.1334
|
Contextual Bandit Learning with Predictable Rewards
|
cs.LG
|
Contextual bandit learning is a reinforcement learning problem where the
learner repeatedly receives a set of features (context), takes an action and
receives a reward based on the action and context. We consider this problem
under a realizability assumption: there exists a function in a (known) function
class, always capable of predicting the expected reward, given the action and
context. Under this assumption, we show three things. We present a new
algorithm---Regressor Elimination--- with a regret similar to the agnostic
setting (i.e. in the absence of realizability assumption). We prove a new lower
bound showing no algorithm can achieve superior performance in the worst case
even with the realizability assumption. However, we do show that for any set of
policies (mapping contexts to actions), there is a distribution over rewards
(given context) such that our new algorithm has constant regret unlike the
previous approaches.
|
1202.1336
|
Reducing complexity of tail-biting trellises
|
cs.IT cs.SY math.IT
|
It is shown that a trellis realization can be locally reduced if it is not
state-trim, branch-trim, proper, observable, and controllable. These conditions
are not sufficient for local irreducibility. Making use of notions that amount
to "almost unobservability/uncontrollability", a necessary and sufficient
criterion of local irreducibility for tail-biting trellises is presented.
|
1202.1337
|
Enhancing the Error Correction of Finite Alphabet Iterative Decoders via
Adaptive Decimation
|
cs.IT math.IT
|
Finite alphabet iterative decoders (FAIDs) for LDPC codes were recently shown
to be capable of surpassing the Belief Propagation (BP) decoder in the error
floor region on the Binary Symmetric channel (BSC). More recently, the
technique of decimation which involves fixing the values of certain bits during
decoding, was proposed for FAIDs in order to make them more amenable to
analysis while maintaining their good performance. In this paper, we show how
decimation can be used adaptively to further enhance the guaranteed error
correction capability of FAIDs that are already good on a given code. The new
adaptive decimation scheme proposed has marginally added complexity but can
significantly improve the slope of the error floor performance of a particular
FAID. We describe the adaptive decimation scheme particularly for 7-level FAIDs
which propagate only 3-bit messages and provide numerical results for
column-weight three codes. Analysis suggests that the failures of the new
decoders are linked to stopping sets of the code.
|
1202.1340
|
An Energy Efficient Semi-static Power Control and Link Adaptation Scheme
in UMTS HSDPA
|
cs.IT math.IT
|
High speed downlink packet access (HSDPA) has been successfully applied in
commercial systems and improves user experience significantly. However, it
incurs substantial energy consumption. In this paper, we address this issue by
proposing a novel energy efficient semi-static power control and link
adaptation scheme in HSDPA. Through estimating the EE under different
modulation and coding schemes (MCSs) and corresponding transmit power, the
proposed scheme can determine the most energy efficient MCS level and transmit
power at the Node B. And then the Node B configure the optimal MCS level and
transmit power. In order to decrease the signaling overhead caused by the
configuration, a dual trigger mechanism is employed. After that, we extend the
proposed scheme to the multiple input multiple output (MIMO) scenarios.
Simulation results confirm the significant EE improvement of our proposed
scheme. Finally, we give a discussion on the potential EE gain and challenge of
the energy efficient mode switching between single input multiple output (SIMO)
and MIMO configuration in HSDPA.
|
1202.1348
|
Selecting Two-Bit Bit Flipping Algorithms for Collective Error
Correction
|
cs.IT math.IT
|
A class of two-bit bit flipping algorithms for decoding low-density
parity-check codes over the binary symmetric channel was proposed in [1].
Initial results showed that decoders which employ a group of these algorithms
operating in parallel can offer low error floor decoding for high-speed
applications. As the number of two-bit bit flipping algorithms is large,
designing such a decoder is not a trivial task. In this paper, we describe a
procedure to select collections of algorithms that work well together. This
procedure relies on a recursive process which enumerates error configurations
that are uncorrectable by a given algorithm. The error configurations
uncorrectable by a given algorithm form its trapping set profile. Based on
their trapping set profiles, algorithms are selected so that in parallel, they
can correct a fixed number of errors with high probability.
|
1202.1354
|
Error Probability Bounds for M-ary Relay Trees
|
cs.IT math.IT
|
We study the detection error probabilities associated with an M-ary relay
tree, where the leaves of the tree correspond to identical and independent
sensors. Only these leaves are sensors. The root of the tree represents a
fusion center that makes the overall detection decision. Each of the other
nodes in the tree is a relay node that combines M summarized messages from its
immediate child nodes to form a single output message using the majority
dominance rule. We derive tight upper and lower bounds for the Type I and II
error probabilities at the fusion center as explicit functions of the number of
sensors in the case of binary message alphabets. These bounds characterize how
fast the error probabilities converge to 0 with respect to the number of
sensors.
|
1202.1367
|
Visualizing Communication on Social Media: Making Big Data Accessible
|
cs.SI physics.soc-ph
|
The broad adoption of the web as a communication medium has made it possible
to study social behavior at a new scale. With social media networks such as
Twitter, we can collect large data sets of online discourse. Social science
researchers and journalists, however, may not have tools available to make
sense of large amounts of data or of the structure of large social networks. In
this paper, we describe our recent extensions to Truthy, a system for
collecting and analyzing political discourse on Twitter. We introduce several
new analytical perspectives on online discourse with the goal of facilitating
collaboration between individuals in the computational and social sciences. The
design decisions described in this article are motivated by real-world use
cases developed in collaboration with colleagues at the Indiana University
School of Journalism.
|
1202.1372
|
Symbolic Models and Control of Discrete-Time Piecewise Affine Systems:
An Approximate Simulation Approach
|
cs.SY
|
Symbolic models have been recently used as a sound mathematical formalism for
the formal verification and control design of purely continuous and hybrid
systems. In this paper we propose a sequence of symbolic models that
approximates a discrete-time Piecewise Affine (PWA) system in the sense of
approximate simulation and converges to the PWA system in the so-called
simulation metric. Symbolic control design is then addressed with
specifications expressed in terms of non-deterministic finite automata. A
sequence of symbolic control strategies is derived which converges, in the
sense of simulation metric, to the maximal controller solving the given
specification on the PWA system.
|
1202.1387
|
Successive Secret Key Agreement over Generalized Multiple Access and
Broadcast Channels
|
cs.IT math.IT
|
A secret key agreement framework between three users is considered in which
each of the users 1 and 2 intends to share a secret key with user 3 and users 1
and 2 are eavesdroppers with respect to each other. There is a generalized
discrete memoryless multiple access channel (GDMMAC) from users 1 and 2 to user
3 where the three users receive outputs from the channel. Furthermore, there is
a broadcast channel (BC) from user 3 to users 1 and 2. Secret key sharing is
intended where GDMMAC and BC can be successively used. In this framework, an
inner bound of the secret key capacity region is derived. Moreover, for a
special case where the channel inputs and outputs of the GDMAC and the BC form
Markov chains in some order, the secret key capacity region is derived. Also
the results are discussed through a binary example.
|
1202.1395
|
Modification of the Elite Ant System in Order to Avoid Local Optimum
Points in the Traveling Salesman Problem
|
cs.AI cs.MA
|
This article presents a new algorithm which is a modified version of the
elite ant system (EAS) algorithm. The new version utilizes an effective
criterion for escaping from the local optimum points. In contrast to the
classical EAC algorithms, the proposed algorithm uses only a global updating,
which will increase pheromone on the edges of the best (i.e. the shortest)
route and will at the same time decrease the amount of pheromone on the edges
of the worst (i.e. the longest) route. In order to assess the efficiency of the
new algorithm, some standard traveling salesman problems (TSPs) were studied
and their results were compared with classical EAC and other well-known
meta-heuristic algorithms. The results indicate that the proposed algorithm has
been able to improve the efficiency of the algorithms in all instances and it
is competitive with other algorithms.
|
1202.1398
|
Classical and Bayesian Linear Data Estimators for Unique Word OFDM
|
cs.IT math.IT
|
Unique word - orthogonal frequency division multiplexing (UW-OFDM) is a novel
OFDM signaling concept, where the guard interval is built of a deterministic
sequence - the so-called unique word - instead of the conventional random
cyclic prefix. In contrast to previous attempts with deterministic sequences in
the guard interval the addressed UW-OFDM signaling approach introduces
correlations between the subcarrier symbols, which can be exploited by the
receiver in order to improve the bit error ratio performance. In this paper we
develop several linear data estimators specifically designed for UW-OFDM, some
based on classical and some based on Bayesian estimation theory. Furthermore,
we derive complexity optimized versions of these estimators, and we study their
individual complex multiplication count in detail. Finally, we evaluate the
estimators' performance for the additive white Gaussian noise channel as well
as for selected indoor multipath channel scenarios.
|
1202.1409
|
Optimization in SMT with LA(Q) Cost Functions
|
cs.AI cs.LO
|
In the contexts of automated reasoning and formal verification, important
decision problems are effectively encoded into Satisfiability Modulo Theories
(SMT). In the last decade efficient SMT solvers have been developed for several
theories of practical interest (e.g., linear arithmetic, arrays, bit-vectors).
Surprisingly, very few work has been done to extend SMT to deal with
optimization problems; in particular, we are not aware of any work on SMT
solvers able to produce solutions which minimize cost functions over
arithmetical variables. This is unfortunate, since some problems of interest
require this functionality.
In this paper we start filling this gap. We present and discuss two general
procedures for leveraging SMT to handle the minimization of LA(Q) cost
functions, combining SMT with standard minimization techniques. We have
implemented the proposed approach within the MathSAT SMT solver. Due to the
lack of competitors in AR and SMT domains, we experimentally evaluated our
implementation against state-of-the-art tools for the domain of linear
generalized disjunctive programming (LGDP), which is closest in spirit to our
domain, on sets of problems which have been previously proposed as benchmarks
for the latter tools. The results show that our tool is very competitive with,
and often outperforms, these tools on these problems, clearly demonstrating the
potential of the approach.
|
1202.1424
|
Optimization in Multi-Frequency Interferometry Ranging: Theory and
Experiment
|
cs.IT math.IT
|
Multi-frequency interferometry (MFI) is well known as an accurate phase-based
measurement scheme. The paper reveals the inherent relationship of the
unambiguous measurement range (UMR), the outlier probability, the MSE
performance with the frequency pattern in MFI system, and then provides the
corresponding criterion for choosing the frequency pattern. We point out that
the theoretical rigorous UMR of MFI deduced in the literature is usually
optimistic for practical application and derive a more practical expression .
It is found that the least-square (LS) estimator of MFI has a distinguished
"double threshold effect". Distinct difference is observed for the MSE in
moderate and high signal-to-noise ratio (SNR) region (denoted by MMSE and HMSE
respectively) and the second threshold effect occurs during the rapid
transition from MMSE to HMSE with increasing SNR. The closed-form expressions
for the MMSE, HMSE and Cramer-Rao bound (CRB) are further derived, with HMSE
coinciding with CRB. Since the HMSE is insensitive to frequency pattern, we
focus on MMSE minimization by proper frequency optimization. We show that a
prime-based frequency interval can be exploited for the purpose of both outlier
suppression and UMR extension and design a special optimal rearrangement for
any set of frequency interval, in the sense of MMSE minimization. An extremely
simple frequency design method is finally developed. Simulation and field
experiment verified that the proposed scheme considerably outperforms the
existing method in UMR as well as MSE performance, especially in the transition
from MMSE to HMSE, for Gaussian and non-Gaussian channel.
|
1202.1444
|
Fully Automatic Expression-Invariant Face Correspondence
|
cs.CV cs.GR
|
We consider the problem of computing accurate point-to-point correspondences
among a set of human face scans with varying expressions. Our fully automatic
approach does not require any manually placed markers on the scan. Instead, the
approach learns the locations of a set of landmarks present in a database and
uses this knowledge to automatically predict the locations of these landmarks
on a newly available scan. The predicted landmarks are then used to compute
point-to-point correspondences between a template model and the newly available
scan. To accurately fit the expression of the template to the expression of the
scan, we use as template a blendshape model. Our algorithm was tested on a
database of human faces of different ethnic groups with strongly varying
expressions. Experimental results show that the obtained point-to-point
correspondence is both highly accurate and consistent for most of the tested 3D
face models.
|
1202.1449
|
On the Coexistence of Macrocell Spatial Multiplexing and Cognitive
Femtocells
|
cs.IT math.IT
|
We study a two-tier macrocell/femtocell system where the macrocell base
station is equipped with multiple antennas and makes use of multiuser MIMO
(spatial multiplexing), and the femtocells are "cognitive". In particular, we
assume that the femtocells are aware of the locations of scheduled macrocell
users on every time-frequency slot, so that they can make decisions on their
transmission opportunities accordingly. Femtocell base stations are also
equipped with multiple antennas. We propose a scheme where the macrocell
downlink (macro- DL) is aligned with the femtocells uplink (femto-UL) and, Vice
Versa, the macrocell uplink (macro-UL) is aligned with the femtocells downlink
femto-DL). Using a simple "interference temperature" power control in the
macro-DL/femto-UL direction, and exploiting uplink/downlink duality and the
Yates, Foschini and Miljanic distributed power control algorithm in the macro-
UL/femto-DL direction, we can achieve an extremely attractive macro/femto
throughput tradeoff region in both directions. We investigate the impact of
multiuser MIMO spatial multiplexing in the macrocell under the proposed scheme,
and find that large gains are achievable by letting the macrocell schedule
groups of co-located users, such that the number of femtocells affected by the
interference temperature power constraint is small.
|
1202.1458
|
A Rate-Compatible Sphere-Packing Analysis of Feedback Coding with
Limited Retransmissions
|
cs.IT math.IT
|
Recent work by Polyanskiy et al. and Chen et al. has excited new interest in
using feedback to approach capacity with low latency. Polyanskiy showed that
feedback identifying the first symbol at which decoding is successful allows
capacity to be approached with surprisingly low latency. This paper uses Chen's
rate-compatible sphere-packing (RCSP) analysis to study what happens when
symbols must be transmitted in packets, as with a traditional hybrid ARQ
system, and limited to relatively few (six or fewer) incremental transmissions.
Numerical optimizations find the series of progressively growing cumulative
block lengths that enable RCSP to approach capacity with the minimum possible
latency. RCSP analysis shows that five incremental transmissions are sufficient
to achieve 92% of capacity with an average block length of fewer than 101
symbols on the AWGN channel with SNR of 2.0 dB.
The RCSP analysis provides a decoding error trajectory that specifies the
decoding error rate for each cumulative block length. Though RCSP is an
idealization, an example tail-biting convolutional code matches the RCSP
decoding error trajectory and achieves 91% of capacity with an average block
length of 102 symbols on the AWGN channel with SNR of 2.0 dB. We also show how
RCSP analysis can be used in cases where packets have deadlines associated with
them (leading to an outage probability).
|
1202.1467
|
Message-Passing Algorithms for Channel Estimation and Decoding Using
Approximate Inference
|
cs.IT math.IT stat.ML
|
We design iterative receiver schemes for a generic wireless communication
system by treating channel estimation and information decoding as an inference
problem in graphical models. We introduce a recently proposed inference
framework that combines belief propagation (BP) and the mean field (MF)
approximation and includes these algorithms as special cases. We also show that
the expectation propagation and expectation maximization algorithms can be
embedded in the BP-MF framework with slight modifications. By applying the
considered inference algorithms to our probabilistic model, we derive four
different message-passing receiver schemes. Our numerical evaluation
demonstrates that the receiver based on the BP-MF framework and its variant
based on BP-EM yield the best compromise between performance, computational
complexity and numerical stability among all candidate algorithms.
|
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