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0704.0046
|
A limit relation for entropy and channel capacity per unit cost
|
quant-ph cs.IT math.IT
|
In a quantum mechanical model, Diosi, Feldmann and Kosloff arrived at a
conjecture stating that the limit of the entropy of certain mixtures is the
relative entropy as system size goes to infinity. The conjecture is proven in
this paper for density matrices. The first proof is analytic and uses the
quantum law of large numbers. The second one clarifies the relation to channel
capacity per unit cost for classical-quantum channels. Both proofs lead to
generalization of the conjecture.
|
0704.0047
|
Intelligent location of simultaneously active acoustic emission sources:
Part I
|
cs.NE cs.AI
|
The intelligent acoustic emission locator is described in Part I, while Part
II discusses blind source separation, time delay estimation and location of two
simultaneously active continuous acoustic emission sources.
The location of acoustic emission on complicated aircraft frame structures is
a difficult problem of non-destructive testing. This article describes an
intelligent acoustic emission source locator. The intelligent locator comprises
a sensor antenna and a general regression neural network, which solves the
location problem based on learning from examples. Locator performance was
tested on different test specimens. Tests have shown that the accuracy of
location depends on sound velocity and attenuation in the specimen, the
dimensions of the tested area, and the properties of stored data. The location
accuracy achieved by the intelligent locator is comparable to that obtained by
the conventional triangulation method, while the applicability of the
intelligent locator is more general since analysis of sonic ray paths is
avoided. This is a promising method for non-destructive testing of aircraft
frame structures by the acoustic emission method.
|
0704.0050
|
Intelligent location of simultaneously active acoustic emission sources:
Part II
|
cs.NE cs.AI
|
Part I describes an intelligent acoustic emission locator, while Part II
discusses blind source separation, time delay estimation and location of two
continuous acoustic emission sources.
Acoustic emission (AE) analysis is used for characterization and location of
developing defects in materials. AE sources often generate a mixture of various
statistically independent signals. A difficult problem of AE analysis is
separation and characterization of signal components when the signals from
various sources and the mode of mixing are unknown. Recently, blind source
separation (BSS) by independent component analysis (ICA) has been used to solve
these problems. The purpose of this paper is to demonstrate the applicability
of ICA to locate two independent simultaneously active acoustic emission
sources on an aluminum band specimen. The method is promising for
non-destructive testing of aircraft frame structures by acoustic emission
analysis.
|
0704.0090
|
Real Options for Project Schedules (ROPS)
|
cs.CE cond-mat.stat-mech cs.MS cs.NA physics.data-an
|
Real Options for Project Schedules (ROPS) has three recursive
sampling/optimization shells. An outer Adaptive Simulated Annealing (ASA)
optimization shell optimizes parameters of strategic Plans containing multiple
Projects containing ordered Tasks. A middle shell samples probability
distributions of durations of Tasks. An inner shell samples probability
distributions of costs of Tasks. PATHTREE is used to develop options on
schedules.. Algorithms used for Trading in Risk Dimensions (TRD) are applied to
develop a relative risk analysis among projects.
|
0704.0098
|
Sparsely-spread CDMA - a statistical mechanics based analysis
|
cs.IT math.IT
|
Sparse Code Division Multiple Access (CDMA), a variation on the standard CDMA
method in which the spreading (signature) matrix contains only a relatively
small number of non-zero elements, is presented and analysed using methods of
statistical physics. The analysis provides results on the performance of
maximum likelihood decoding for sparse spreading codes in the large system
limit. We present results for both cases of regular and irregular spreading
matrices for the binary additive white Gaussian noise channel (BIAWGN) with a
comparison to the canonical (dense) random spreading code.
|
0704.0217
|
Capacity of a Multiple-Antenna Fading Channel with a Quantized Precoding
Matrix
|
cs.IT math.IT
|
Given a multiple-input multiple-output (MIMO) channel, feedback from the
receiver can be used to specify a transmit precoding matrix, which selectively
activates the strongest channel modes. Here we analyze the performance of
Random Vector Quantization (RVQ), in which the precoding matrix is selected
from a random codebook containing independent, isotropically distributed
entries. We assume that channel elements are i.i.d. and known to the receiver,
which relays the optimal (rate-maximizing) precoder codebook index to the
transmitter using B bits. We first derive the large system capacity of
beamforming (rank-one precoding matrix) as a function of B, where large system
refers to the limit as B and the number of transmit and receive antennas all go
to infinity with fixed ratios. With beamforming RVQ is asymptotically optimal,
i.e., no other quantization scheme can achieve a larger asymptotic rate. The
performance of RVQ is also compared with that of a simpler reduced-rank scalar
quantization scheme in which the beamformer is constrained to lie in a random
subspace. We subsequently consider a precoding matrix with arbitrary rank, and
approximate the asymptotic RVQ performance with optimal and linear receivers
(matched filter and Minimum Mean Squared Error (MMSE)). Numerical examples show
that these approximations accurately predict the performance of finite-size
systems of interest. Given a target spectral efficiency, numerical examples
show that the amount of feedback required by the linear MMSE receiver is only
slightly more than that required by the optimal receiver, whereas the matched
filter can require significantly more feedback.
|
0704.0282
|
On Punctured Pragmatic Space-Time Codes in Block Fading Channel
|
cs.IT cs.CC math.IT
|
This paper considers the use of punctured convolutional codes to obtain
pragmatic space-time trellis codes over block-fading channel. We show that good
performance can be achieved even when puncturation is adopted and that we can
still employ the same Viterbi decoder of the convolutional mother code by using
approximated metrics without increasing the complexity of the decoding
operations.
|
0704.0304
|
The World as Evolving Information
|
cs.IT cs.AI math.IT q-bio.PE
|
This paper discusses the benefits of describing the world as information,
especially in the study of the evolution of life and cognition. Traditional
studies encounter problems because it is difficult to describe life and
cognition in terms of matter and energy, since their laws are valid only at the
physical scale. However, if matter and energy, as well as life and cognition,
are described in terms of information, evolution can be described consistently
as information becoming more complex.
The paper presents eight tentative laws of information, valid at multiple
scales, which are generalizations of Darwinian, cybernetic, thermodynamic,
psychological, philosophical, and complexity principles. These are further used
to discuss the notions of life, cognition and their evolution.
|
0704.0361
|
Pseudo-random Puncturing: A Technique to Lower the Error Floor of Turbo
Codes
|
cs.IT math.IT
|
It has been observed that particular rate-1/2 partially systematic parallel
concatenated convolutional codes (PCCCs) can achieve a lower error floor than
that of their rate-1/3 parent codes. Nevertheless, good puncturing patterns can
only be identified by means of an exhaustive search, whilst convergence towards
low bit error probabilities can be problematic when the systematic output of a
rate-1/2 partially systematic PCCC is heavily punctured. In this paper, we
present and study a family of rate-1/2 partially systematic PCCCs, which we
call pseudo-randomly punctured codes. We evaluate their bit error rate
performance and we show that they always yield a lower error floor than that of
their rate-1/3 parent codes. Furthermore, we compare analytic results to
simulations and we demonstrate that their performance converges towards the
error floor region, owning to the moderate puncturing of their systematic
output. Consequently, we propose pseudo-random puncturing as a means of
improving the bandwidth efficiency of a PCCC and simultaneously lowering its
error floor.
|
0704.0499
|
Optimal Routing for Decode-and-Forward based Cooperation in Wireless
Networks
|
cs.IT math.IT
|
We investigate cooperative wireless relay networks in which the nodes can
help each other in data transmission. We study different coding strategies in
the single-source single-destination network with many relay nodes. Given the
myriad of ways in which nodes can cooperate, there is a natural routing
problem, i.e., determining an ordered set of nodes to relay the data from the
source to the destination. We find that for a given route, the
decode-and-forward strategy, which is an information theoretic cooperative
coding strategy, achieves rates significantly higher than that achievable by
the usual multi-hop coding strategy, which is a point-to-point non-cooperative
coding strategy. We construct an algorithm to find an optimal route (in terms
of rate maximizing) for the decode-and-forward strategy. Since the algorithm
runs in factorial time in the worst case, we propose a heuristic algorithm that
runs in polynomial time. The heuristic algorithm outputs an optimal route when
the nodes transmit independent codewords. We implement these coding strategies
using practical low density parity check codes to compare the performance of
the strategies on different routes.
|
0704.0528
|
Many-to-One Throughput Capacity of IEEE 802.11 Multi-hop Wireless
Networks
|
cs.NI cs.IT math.IT
|
This paper investigates the many-to-one throughput capacity (and by symmetry,
one-to-many throughput capacity) of IEEE 802.11 multi-hop networks. It has
generally been assumed in prior studies that the many-to-one throughput
capacity is upper-bounded by the link capacity L. Throughput capacity L is not
achievable under 802.11. This paper introduces the notion of "canonical
networks", which is a class of regularly-structured networks whose capacities
can be analyzed more easily than unstructured networks. We show that the
throughput capacity of canonical networks under 802.11 has an analytical upper
bound of 3L/4 when the source nodes are two or more hops away from the sink;
and simulated throughputs of 0.690L (0.740L) when the source nodes are many
hops away. We conjecture that 3L/4 is also the upper bound for general
networks. When all links have equal length, 2L/3 can be shown to be the upper
bound for general networks. Our simulations show that 802.11 networks with
random topologies operated with AODV routing can only achieve throughputs far
below the upper bounds. Fortunately, by properly selecting routes near the
gateway (or by properly positioning the relay nodes leading to the gateway) to
fashion after the structure of canonical networks, the throughput can be
improved significantly by more than 150%. Indeed, in a dense network, it is
worthwhile to deactivate some of the relay nodes near the sink judiciously.
|
0704.0540
|
On the Achievable Rate Regions for Interference Channels with Degraded
Message Sets
|
cs.IT math.IT
|
The interference channel with degraded message sets (IC-DMS) refers to a
communication model in which two senders attempt to communicate with their
respective receivers simultaneously through a common medium, and one of the
senders has complete and a priori (non-causal) knowledge about the message
being transmitted by the other. A coding scheme that collectively has
advantages of cooperative coding, collaborative coding, and dirty paper coding,
is developed for such a channel. With resorting to this coding scheme,
achievable rate regions of the IC-DMS in both discrete memoryless and Gaussian
cases are derived, which, in general, include several previously known rate
regions. Numerical examples for the Gaussian case demonstrate that in the
high-interference-gain regime, the derived achievable rate regions offer
considerable improvements over these existing results.
|
0704.0590
|
A Low Complexity Algorithm and Architecture for Systematic Encoding of
Hermitian Codes
|
cs.IT math.IT
|
We present an algorithm for systematic encoding of Hermitian codes. For a
Hermitian code defined over GF(q^2), the proposed algorithm achieves a run time
complexity of O(q^2) and is suitable for VLSI implementation. The encoder
architecture uses as main blocks q varying-rate Reed-Solomon encoders and
achieves a space complexity of O(q^2) in terms of finite field multipliers and
memory elements.
|
0704.0671
|
Learning from compressed observations
|
cs.IT cs.LG math.IT
|
The problem of statistical learning is to construct a predictor of a random
variable $Y$ as a function of a related random variable $X$ on the basis of an
i.i.d. training sample from the joint distribution of $(X,Y)$. Allowable
predictors are drawn from some specified class, and the goal is to approach
asymptotically the performance (expected loss) of the best predictor in the
class. We consider the setting in which one has perfect observation of the
$X$-part of the sample, while the $Y$-part has to be communicated at some
finite bit rate. The encoding of the $Y$-values is allowed to depend on the
$X$-values. Under suitable regularity conditions on the admissible predictors,
the underlying family of probability distributions and the loss function, we
give an information-theoretic characterization of achievable predictor
performance in terms of conditional distortion-rate functions. The ideas are
illustrated on the example of nonparametric regression in Gaussian noise.
|
0704.0802
|
Hybrid-ARQ in Multihop Networks with Opportunistic Relay Selection
|
cs.IT math.IT
|
This paper develops a contention-based opportunistic feedback technique
towards relay selection in a dense wireless network. This technique enables the
forwarding of additional parity information from the selected relay to the
destination. For a given network, the effects of varying key parameters such as
the feedback probability are presented and discussed. A primary advantage of
the proposed technique is that relay selection can be performed in a
distributed way. Simulation results find its performance to closely match that
of centralized schemes that utilize GPS information, unlike the proposed
method. The proposed relay selection method is also found to achieve throughput
gains over a point-to-point transmission strategy.
|
0704.0805
|
Opportunistic Relay Selection with Limited Feedback
|
cs.IT math.IT
|
It has been shown that a decentralized relay selection protocol based on
opportunistic feedback from the relays yields good throughput performance in
dense wireless networks. This selection strategy supports a hybrid-ARQ
transmission approach where relays forward parity information to the
destination in the event of a decoding error. Such an approach, however,
suffers a loss compared to centralized strategies that select relays with the
best channel gain to the destination. This paper closes the performance gap by
adding another level of channel feedback to the decentralized relay selection
problem. It is demonstrated that only one additional bit of feedback is
necessary for good throughput performance. The performance impact of varying
key parameters such as the number of relays and the channel feedback threshold
is discussed. An accompanying bit error rate analysis demonstrates the
importance of relay selection.
|
0704.0831
|
On packet lengths and overhead for random linear coding over the erasure
channel
|
cs.IT math.IT
|
We assess the practicality of random network coding by illuminating the issue
of overhead and considering it in conjunction with increasingly long packets
sent over the erasure channel. We show that the transmission of increasingly
long packets, consisting of either of an increasing number of symbols per
packet or an increasing symbol alphabet size, results in a data rate
approaching zero over the erasure channel. This result is due to an erasure
probability that increases with packet length. Numerical results for a
particular modulation scheme demonstrate a data rate of approximately zero for
a large, but finite-length packet. Our results suggest a reduction in the
performance gains offered by random network coding.
|
0704.0838
|
Universal Source Coding for Monotonic and Fast Decaying Monotonic
Distributions
|
cs.IT math.IT
|
We study universal compression of sequences generated by monotonic
distributions. We show that for a monotonic distribution over an alphabet of
size $k$, each probability parameter costs essentially $0.5 \log (n/k^3)$ bits,
where $n$ is the coded sequence length, as long as $k = o(n^{1/3})$. Otherwise,
for $k = O(n)$, the total average sequence redundancy is $O(n^{1/3+\epsilon})$
bits overall. We then show that there exists a sub-class of monotonic
distributions over infinite alphabets for which redundancy of
$O(n^{1/3+\epsilon})$ bits overall is still achievable. This class contains
fast decaying distributions, including many distributions over the integers and
geometric distributions. For some slower decays, including other distributions
over the integers, redundancy of $o(n)$ bits overall is achievable, where a
method to compute specific redundancy rates for such distributions is derived.
The results are specifically true for finite entropy monotonic distributions.
Finally, we study individual sequence redundancy behavior assuming a sequence
is governed by a monotonic distribution. We show that for sequences whose
empirical distributions are monotonic, individual redundancy bounds similar to
those in the average case can be obtained. However, even if the monotonicity in
the empirical distribution is violated, diminishing per symbol individual
sequence redundancies with respect to the monotonic maximum likelihood
description length may still be achievable.
|
0704.0954
|
Sensor Networks with Random Links: Topology Design for Distributed
Consensus
|
cs.IT cs.LG math.IT
|
In a sensor network, in practice, the communication among sensors is subject
to:(1) errors or failures at random times; (3) costs; and(2) constraints since
sensors and networks operate under scarce resources, such as power, data rate,
or communication. The signal-to-noise ratio (SNR) is usually a main factor in
determining the probability of error (or of communication failure) in a link.
These probabilities are then a proxy for the SNR under which the links operate.
The paper studies the problem of designing the topology, i.e., assigning the
probabilities of reliable communication among sensors (or of link failures) to
maximize the rate of convergence of average consensus, when the link
communication costs are taken into account, and there is an overall
communication budget constraint. To consider this problem, we address a number
of preliminary issues: (1) model the network as a random topology; (2)
establish necessary and sufficient conditions for mean square sense (mss) and
almost sure (a.s.) convergence of average consensus when network links fail;
and, in particular, (3) show that a necessary and sufficient condition for both
mss and a.s. convergence is for the algebraic connectivity of the mean graph
describing the network topology to be strictly positive. With these results, we
formulate topology design, subject to random link failures and to a
communication cost constraint, as a constrained convex optimization problem to
which we apply semidefinite programming techniques. We show by an extensive
numerical study that the optimal design improves significantly the convergence
speed of the consensus algorithm and can achieve the asymptotic performance of
a non-random network at a fraction of the communication cost.
|
0704.0967
|
Cross-Layer Optimization of MIMO-Based Mesh Networks with Gaussian
Vector Broadcast Channels
|
cs.IT cs.AR math.IT
|
MIMO technology is one of the most significant advances in the past decade to
increase channel capacity and has a great potential to improve network capacity
for mesh networks. In a MIMO-based mesh network, the links outgoing from each
node sharing the common communication spectrum can be modeled as a Gaussian
vector broadcast channel. Recently, researchers showed that ``dirty paper
coding'' (DPC) is the optimal transmission strategy for Gaussian vector
broadcast channels. So far, there has been little study on how this fundamental
result will impact the cross-layer design for MIMO-based mesh networks. To fill
this gap, we consider the problem of jointly optimizing DPC power allocation in
the link layer at each node and multihop/multipath routing in a MIMO-based mesh
networks. It turns out that this optimization problem is a very challenging
non-convex problem. To address this difficulty, we transform the original
problem to an equivalent problem by exploiting the channel duality. For the
transformed problem, we develop an efficient solution procedure that integrates
Lagrangian dual decomposition method, conjugate gradient projection method
based on matrix differential calculus, cutting-plane method, and subgradient
method. In our numerical example, it is shown that we can achieve a network
performance gain of 34.4% by using DPC.
|
0704.0985
|
Architecture for Pseudo Acausal Evolvable Embedded Systems
|
cs.NE cs.AI
|
Advances in semiconductor technology are contributing to the increasing
complexity in the design of embedded systems. Architectures with novel
techniques such as evolvable nature and autonomous behavior have engrossed lot
of attention. This paper demonstrates conceptually evolvable embedded systems
can be characterized basing on acausal nature. It is noted that in acausal
systems, future input needs to be known, here we make a mechanism such that the
system predicts the future inputs and exhibits pseudo acausal nature. An
embedded system that uses theoretical framework of acausality is proposed. Our
method aims at a novel architecture that features the hardware evolability and
autonomous behavior alongside pseudo acausality. Various aspects of this
architecture are discussed in detail along with the limitations.
|
0704.1020
|
The on-line shortest path problem under partial monitoring
|
cs.LG cs.SC
|
The on-line shortest path problem is considered under various models of
partial monitoring. Given a weighted directed acyclic graph whose edge weights
can change in an arbitrary (adversarial) way, a decision maker has to choose in
each round of a game a path between two distinguished vertices such that the
loss of the chosen path (defined as the sum of the weights of its composing
edges) be as small as possible. In a setting generalizing the multi-armed
bandit problem, after choosing a path, the decision maker learns only the
weights of those edges that belong to the chosen path. For this problem, an
algorithm is given whose average cumulative loss in n rounds exceeds that of
the best path, matched off-line to the entire sequence of the edge weights, by
a quantity that is proportional to 1/\sqrt{n} and depends only polynomially on
the number of edges of the graph. The algorithm can be implemented with linear
complexity in the number of rounds n and in the number of edges. An extension
to the so-called label efficient setting is also given, in which the decision
maker is informed about the weights of the edges corresponding to the chosen
path at a total of m << n time instances. Another extension is shown where the
decision maker competes against a time-varying path, a generalization of the
problem of tracking the best expert. A version of the multi-armed bandit
setting for shortest path is also discussed where the decision maker learns
only the total weight of the chosen path but not the weights of the individual
edges on the path. Applications to routing in packet switched networks along
with simulation results are also presented.
|
0704.1028
|
A neural network approach to ordinal regression
|
cs.LG cs.AI cs.NE
|
Ordinal regression is an important type of learning, which has properties of
both classification and regression. Here we describe a simple and effective
approach to adapt a traditional neural network to learn ordinal categories. Our
approach is a generalization of the perceptron method for ordinal regression.
On several benchmark datasets, our method (NNRank) outperforms a neural network
classification method. Compared with the ordinal regression methods using
Gaussian processes and support vector machines, NNRank achieves comparable
performance. Moreover, NNRank has the advantages of traditional neural
networks: learning in both online and batch modes, handling very large training
datasets, and making rapid predictions. These features make NNRank a useful and
complementary tool for large-scale data processing tasks such as information
retrieval, web page ranking, collaborative filtering, and protein ranking in
Bioinformatics.
|
0704.1043
|
On the Kolmogorov-Chaitin Complexity for short sequences
|
cs.CC cs.IT math.IT
|
A drawback of Kolmogorov-Chaitin complexity (K) as a function from s to the
shortest program producing s is its noncomputability which limits its range of
applicability. Moreover, when strings are short, the dependence of K on a
particular universal Turing machine U can be arbitrary. In practice one can
approximate it by computable compression methods. However, such compression
methods do not always provide meaningful approximations--for strings shorter,
for example, than typical compiler lengths. In this paper we suggest an
empirical approach to overcome this difficulty and to obtain a stable
definition of the Kolmogorov-Chaitin complexity for short sequences.
Additionally, a correlation in terms of distribution frequencies was found
across the output of two models of abstract machines, namely unidimensional
cellular automata and deterministic Turing machine.
|
0704.1070
|
Differential Diversity Reception of MDPSK over Independent Rayleigh
Channels with Nonidentical Branch Statistics and Asymmetric Fading Spectrum
|
cs.IT cs.PF math.IT
|
This paper is concerned with optimum diversity receiver structure and its
performance analysis of differential phase shift keying (DPSK) with
differential detection over nonselective, independent, nonidentically
distributed, Rayleigh fading channels. The fading process in each branch is
assumed to have an arbitrary Doppler spectrum with arbitrary Doppler bandwidth,
but to have distinct, asymmetric fading power spectral density characteristic.
Using 8-DPSK as an example, the average bit error probability (BEP) of the
optimum diversity receiver is obtained by calculating the BEP for each of the
three individual bits. The BEP results derived are given in exact, explicit,
closed-form expressions which show clearly the behavior of the performance as a
function of various system parameters.
|
0704.1158
|
Novelty and Collective Attention
|
cs.CY cs.IR physics.soc-ph
|
The subject of collective attention is central to an information age where
millions of people are inundated with daily messages. It is thus of interest to
understand how attention to novel items propagates and eventually fades among
large populations. We have analyzed the dynamics of collective attention among
one million users of an interactive website -- \texttt{digg.com} -- devoted to
thousands of novel news stories. The observations can be described by a
dynamical model characterized by a single novelty factor. Our measurements
indicate that novelty within groups decays with a stretched-exponential law,
suggesting the existence of a natural time scale over which attention fades.
|
0704.1196
|
Novel algorithm to calculate hypervolume indicator of Pareto
approximation set
|
cs.CG cs.NE
|
Hypervolume indicator is a commonly accepted quality measure for comparing
Pareto approximation set generated by multi-objective optimizers. The best
known algorithm to calculate it for $n$ points in $d$-dimensional space has a
run time of $O(n^{d/2})$ with special data structures. This paper presents a
recursive, vertex-splitting algorithm for calculating the hypervolume indicator
of a set of $n$ non-comparable points in $d>2$ dimensions. It splits out
multiple child hyper-cuboids which can not be dominated by a splitting
reference point. In special, the splitting reference point is carefully chosen
to minimize the number of points in the child hyper-cuboids. The complexity
analysis shows that the proposed algorithm achieves $O((\frac{d}{2})^n)$ time
and $O(dn^2)$ space complexity in the worst case.
|
0704.1198
|
A Doubly Distributed Genetic Algorithm for Network Coding
|
cs.NE cs.NI
|
We present a genetic algorithm which is distributed in two novel ways: along
genotype and temporal axes. Our algorithm first distributes, for every member
of the population, a subset of the genotype to each network node, rather than a
subset of the population to each. This genotype distribution is shown to offer
a significant gain in running time. Then, for efficient use of the
computational resources in the network, our algorithm divides the candidate
solutions into pipelined sets and thus the distribution is in the temporal
domain, rather that in the spatial domain. This temporal distribution may lead
to temporal inconsistency in selection and replacement, however our experiments
yield better efficiency in terms of the time to convergence without incurring
significant penalties.
|
0704.1267
|
Text Line Segmentation of Historical Documents: a Survey
|
cs.CV
|
There is a huge amount of historical documents in libraries and in various
National Archives that have not been exploited electronically. Although
automatic reading of complete pages remains, in most cases, a long-term
objective, tasks such as word spotting, text/image alignment, authentication
and extraction of specific fields are in use today. For all these tasks, a
major step is document segmentation into text lines. Because of the low quality
and the complexity of these documents (background noise, artifacts due to
aging, interfering lines),automatic text line segmentation remains an open
research field. The objective of this paper is to present a survey of existing
methods, developed during the last decade, and dedicated to documents of
historical interest.
|
0704.1274
|
Parametric Learning and Monte Carlo Optimization
|
cs.LG
|
This paper uncovers and explores the close relationship between Monte Carlo
Optimization of a parametrized integral (MCO), Parametric machine-Learning
(PL), and `blackbox' or `oracle'-based optimization (BO). We make four
contributions. First, we prove that MCO is mathematically identical to a broad
class of PL problems. This identity potentially provides a new application
domain for all broadly applicable PL techniques: MCO. Second, we introduce
immediate sampling, a new version of the Probability Collectives (PC) algorithm
for blackbox optimization. Immediate sampling transforms the original BO
problem into an MCO problem. Accordingly, by combining these first two
contributions, we can apply all PL techniques to BO. In our third contribution
we validate this way of improving BO by demonstrating that cross-validation and
bagging improve immediate sampling. Finally, conventional MC and MCO procedures
ignore the relationship between the sample point locations and the associated
values of the integrand; only the values of the integrand at those locations
are considered. We demonstrate that one can exploit the sample location
information using PL techniques, for example by forming a fit of the sample
locations to the associated values of the integrand. This provides an
additional way to apply PL techniques to improve MCO.
|
0704.1308
|
Antenna Combining for the MIMO Downlink Channel
|
cs.IT math.IT
|
A multiple antenna downlink channel where limited channel feedback is
available to the transmitter is considered. In a vector downlink channel
(single antenna at each receiver), the transmit antenna array can be used to
transmit separate data streams to multiple receivers only if the transmitter
has very accurate channel knowledge, i.e., if there is high-rate channel
feedback from each receiver. In this work it is shown that channel feedback
requirements can be significantly reduced if each receiver has a small number
of antennas and appropriately combines its antenna outputs. A combining method
that minimizes channel quantization error at each receiver, and thereby
minimizes multi-user interference, is proposed and analyzed. This technique is
shown to outperform traditional techniques such as maximum-ratio combining
because minimization of interference power is more critical than maximization
of signal power in the multiple antenna downlink. Analysis is provided to
quantify the feedback savings, and the technique is seen to work well with user
selection and is also robust to receiver estimation error.
|
0704.1317
|
Low Density Lattice Codes
|
cs.IT math.IT
|
Low density lattice codes (LDLC) are novel lattice codes that can be decoded
efficiently and approach the capacity of the additive white Gaussian noise
(AWGN) channel. In LDLC a codeword x is generated directly at the n-dimensional
Euclidean space as a linear transformation of a corresponding integer message
vector b, i.e., x = Gb, where H, the inverse of G, is restricted to be sparse.
The fact that H is sparse is utilized to develop a linear-time iterative
decoding scheme which attains, as demonstrated by simulations, good error
performance within ~0.5dB from capacity at block length of n = 100,000 symbols.
The paper also discusses convergence results and implementation considerations.
|
0704.1353
|
Supporting Knowledge and Expertise Finding within Australia's Defence
Science and Technology Organisation
|
cs.OH cs.DB cs.DL cs.HC
|
This paper reports on work aimed at supporting knowledge and expertise
finding within a large Research and Development (R&D) organisation. The paper
first discusses the nature of knowledge important to R&D organisations and
presents a prototype information system developed to support knowledge and
expertise finding. The paper then discusses a trial of the system within an R&D
organisation, the implications and limitations of the trial, and discusses
future research questions.
|
0704.1358
|
Distance preserving mappings from ternary vectors to permutations
|
cs.DM cs.IT math.IT
|
Distance-preserving mappings (DPMs) are mappings from the set of all q-ary
vectors of a fixed length to the set of permutations of the same or longer
length such that every two distinct vectors are mapped to permutations with the
same or even larger Hamming distance than that of the vectors. In this paper,
we propose a construction of DPMs from ternary vectors. The constructed DPMs
improve the lower bounds on the maximal size of permutation arrays.
|
0704.1394
|
Calculating Valid Domains for BDD-Based Interactive Configuration
|
cs.AI
|
In these notes we formally describe the functionality of Calculating Valid
Domains from the BDD representing the solution space of valid configurations.
The formalization is largely based on the CLab configuration framework.
|
0704.1409
|
Preconditioned Temporal Difference Learning
|
cs.LG cs.AI
|
This paper has been withdrawn by the author. This draft is withdrawn for its
poor quality in english, unfortunately produced by the author when he was just
starting his science route. Look at the ICML version instead:
http://icml2008.cs.helsinki.fi/papers/111.pdf
|
0704.1411
|
Trellis-Coded Quantization Based on Maximum-Hamming-Distance Binary
Codes
|
cs.IT math.IT
|
Most design approaches for trellis-coded quantization take advantage of the
duality of trellis-coded quantization with trellis-coded modulation, and use
the same empirically-found convolutional codes to label the trellis branches.
This letter presents an alternative approach that instead takes advantage of
maximum-Hamming-distance convolutional codes. The proposed source codes are
shown to be competitive with the best in the literature for the same
computational complexity.
|
0704.1455
|
A Better Good-Turing Estimator for Sequence Probabilities
|
cs.IT math.IT
|
We consider the problem of estimating the probability of an observed string
drawn i.i.d. from an unknown distribution. The key feature of our study is that
the length of the observed string is assumed to be of the same order as the
size of the underlying alphabet. In this setting, many letters are unseen and
the empirical distribution tends to overestimate the probability of the
observed letters. To overcome this problem, the traditional approach to
probability estimation is to use the classical Good-Turing estimator. We
introduce a natural scaling model and use it to show that the Good-Turing
sequence probability estimator is not consistent. We then introduce a novel
sequence probability estimator that is indeed consistent under the natural
scaling model.
|
0704.1524
|
GLRT-Optimal Noncoherent Lattice Decoding
|
cs.IT math.IT
|
This paper presents new low-complexity lattice-decoding algorithms for
noncoherent block detection of QAM and PAM signals over complex-valued fading
channels. The algorithms are optimal in terms of the generalized likelihood
ratio test (GLRT). The computational complexity is polynomial in the block
length; making GLRT-optimal noncoherent detection feasible for implementation.
We also provide even lower complexity suboptimal algorithms. Simulations show
that the suboptimal algorithms have performance indistinguishable from the
optimal algorithms. Finally, we consider block based transmission, and propose
to use noncoherent detection as an alternative to pilot assisted transmission
(PAT). The new technique is shown to outperform PAT.
|
0704.1675
|
Exploiting Social Annotation for Automatic Resource Discovery
|
cs.AI cs.CY cs.DL
|
Information integration applications, such as mediators or mashups, that
require access to information resources currently rely on users manually
discovering and integrating them in the application. Manual resource discovery
is a slow process, requiring the user to sift through results obtained via
keyword-based search. Although search methods have advanced to include evidence
from document contents, its metadata and the contents and link structure of the
referring pages, they still do not adequately cover information sources --
often called ``the hidden Web''-- that dynamically generate documents in
response to a query. The recently popular social bookmarking sites, which allow
users to annotate and share metadata about various information sources, provide
rich evidence for resource discovery. In this paper, we describe a
probabilistic model of the user annotation process in a social bookmarking
system del.icio.us. We then use the model to automatically find resources
relevant to a particular information domain. Our experimental results on data
obtained from \emph{del.icio.us} show this approach as a promising method for
helping automate the resource discovery task.
|
0704.1676
|
Personalizing Image Search Results on Flickr
|
cs.IR cs.AI cs.CY cs.DL cs.HC
|
The social media site Flickr allows users to upload their photos, annotate
them with tags, submit them to groups, and also to form social networks by
adding other users as contacts. Flickr offers multiple ways of browsing or
searching it. One option is tag search, which returns all images tagged with a
specific keyword. If the keyword is ambiguous, e.g., ``beetle'' could mean an
insect or a car, tag search results will include many images that are not
relevant to the sense the user had in mind when executing the query. We claim
that users express their photography interests through the metadata they add in
the form of contacts and image annotations. We show how to exploit this
metadata to personalize search results for the user, thereby improving search
performance. First, we show that we can significantly improve search precision
by filtering tag search results by user's contacts or a larger social network
that includes those contact's contacts. Secondly, we describe a probabilistic
model that takes advantage of tag information to discover latent topics
contained in the search results. The users' interests can similarly be
described by the tags they used for annotating their images. The latent topics
found by the model are then used to personalize search results by finding
images on topics that are of interest to the user.
|
0704.1709
|
Traitement Des Donnees Manquantes Au Moyen De L'Algorithme De Kohonen
|
stat.AP cs.NE
|
Nous montrons comment il est possible d'utiliser l'algorithme d'auto
organisation de Kohonen pour traiter des donn\'ees avec valeurs manquantes et
estimer ces derni\`eres. Apr\`es un rappel m\'ethodologique, nous illustrons
notre propos \`a partir de trois applications \`a des donn\'ees r\'eelles.
-----
We show how it is possible to use the Kohonen self-organizing algorithm to
deal with data which contain missing values and to estimate them. After a
methodological recall, we illustrate our purpose from three real databases
applications.
|
0704.1751
|
Information Theoretic Proofs of Entropy Power Inequalities
|
cs.IT math.IT
|
While most useful information theoretic inequalities can be deduced from the
basic properties of entropy or mutual information, up to now Shannon's entropy
power inequality (EPI) is an exception: Existing information theoretic proofs
of the EPI hinge on representations of differential entropy using either Fisher
information or minimum mean-square error (MMSE), which are derived from de
Bruijn's identity. In this paper, we first present an unified view of these
proofs, showing that they share two essential ingredients: 1) a data processing
argument applied to a covariance-preserving linear transformation; 2) an
integration over a path of a continuous Gaussian perturbation. Using these
ingredients, we develop a new and brief proof of the EPI through a mutual
information inequality, which replaces Stam and Blachman's Fisher information
inequality (FII) and an inequality for MMSE by Guo, Shamai and Verd\'u used in
earlier proofs. The result has the advantage of being very simple in that it
relies only on the basic properties of mutual information. These ideas are then
generalized to various extended versions of the EPI: Zamir and Feder's
generalized EPI for linear transformations of the random variables, Takano and
Johnson's EPI for dependent variables, Liu and Viswanath's
covariance-constrained EPI, and Costa's concavity inequality for the entropy
power.
|
0704.1768
|
Assessment and Propagation of Input Uncertainty in Tree-based Option
Pricing Models
|
cs.CE cs.GT
|
This paper aims to provide a practical example on the assessment and
propagation of input uncertainty for option pricing when using tree-based
methods. Input uncertainty is propagated into output uncertainty, reflecting
that option prices are as unknown as the inputs they are based on. Option
pricing formulas are tools whose validity is conditional not only on how close
the model represents reality, but also on the quality of the inputs they use,
and those inputs are usually not observable. We provide three alternative
frameworks to calibrate option pricing tree models, propagating parameter
uncertainty into the resulting option prices. We finally compare our methods
with classical calibration-based results assuming that there is no options
market established. These methods can be applied to pricing of instruments for
which there is not an options market, as well as a methodological tool to
account for parameter and model uncertainty in theoretical option pricing.
|
0704.1783
|
Unicast and Multicast Qos Routing with Soft Constraint Logic Programming
|
cs.LO cs.AI cs.NI
|
We present a formal model to represent and solve the unicast/multicast
routing problem in networks with Quality of Service (QoS) requirements. To
attain this, first we translate the network adapting it to a weighted graph
(unicast) or and-or graph (multicast), where the weight on a connector
corresponds to the multidimensional cost of sending a packet on the related
network link: each component of the weights vector represents a different QoS
metric value (e.g. bandwidth, cost, delay, packet loss). The second step
consists in writing this graph as a program in Soft Constraint Logic
Programming (SCLP): the engine of this framework is then able to find the best
paths/trees by optimizing their costs and solving the constraints imposed on
them (e.g. delay < 40msec), thus finding a solution to QoS routing problems.
Moreover, c-semiring structures are a convenient tool to model QoS metrics. At
last, we provide an implementation of the framework over scale-free networks
and we suggest how the performance can be improved.
|
0704.1818
|
Low-density graph codes that are optimal for source/channel coding and
binning
|
cs.IT math.IT
|
We describe and analyze the joint source/channel coding properties of a class
of sparse graphical codes based on compounding a low-density generator matrix
(LDGM) code with a low-density parity check (LDPC) code. Our first pair of
theorems establish that there exist codes from this ensemble, with all degrees
remaining bounded independently of block length, that are simultaneously
optimal as both source and channel codes when encoding and decoding are
performed optimally. More precisely, in the context of lossy compression, we
prove that finite degree constructions can achieve any pair $(R, D)$ on the
rate-distortion curve of the binary symmetric source. In the context of channel
coding, we prove that finite degree codes can achieve any pair $(C, p)$ on the
capacity-noise curve of the binary symmetric channel. Next, we show that our
compound construction has a nested structure that can be exploited to achieve
the Wyner-Ziv bound for source coding with side information (SCSI), as well as
the Gelfand-Pinsker bound for channel coding with side information (CCSI).
Although the current results are based on optimal encoding and decoding, the
proposed graphical codes have sparse structure and high girth that renders them
well-suited to message-passing and other efficient decoding procedures.
|
0704.1873
|
An Achievable Rate Region for Interference Channels with Conferencing
|
cs.IT math.IT
|
In this paper, we propose an achievable rate region for discrete memoryless
interference channels with conferencing at the transmitter side. We employ
superposition block Markov encoding, combined with simultaneous superposition
coding, dirty paper coding, and random binning to obtain the achievable rate
region. We show that, under respective conditions, the proposed achievable
region reduces to Han and Kobayashi achievable region for interference
channels, the capacity region for degraded relay channels, and the capacity
region for the Gaussian vector broadcast channel. Numerical examples for the
Gaussian case are given.
|
0704.1925
|
Blind Identification of Distributed Antenna Systems with Multiple
Carrier Frequency Offsets
|
cs.IT math.IT
|
In spatially distributed multiuser antenna systems, the received signal
contains multiple carrier-frequency offsets (CFOs) arising from mismatch
between the oscillators of transmitters and receivers. This results in a
time-varying rotation of the data constellation, which needs to be compensated
at the receiver before symbol recovery. In this paper, a new approach for blind
CFO estimation and symbol recovery is proposed. The received base-band signal
is over-sampled, and its polyphase components are used to formulate a virtual
Multiple-Input Multiple-Output (MIMO) problem. By applying blind MIMO system
estimation techniques, the system response can be estimated and decoupled
versions of the user symbols can be recovered, each one of which contains a
distinct CFO. By applying a decision feedback Phase Lock Loop (PLL), the CFO
can be mitigated and the transmitted symbols can be recovered. The estimated
MIMO system response provides information about the CFOs that can be used to
initialize the PLL, speed up its convergence, and avoid ambiguities usually
linked with PLL.
|
0704.2010
|
A study of structural properties on profiles HMMs
|
cs.AI
|
Motivation: Profile hidden Markov Models (pHMMs) are a popular and very
useful tool in the detection of the remote homologue protein families.
Unfortunately, their performance is not always satisfactory when proteins are
in the 'twilight zone'. We present HMMER-STRUCT, a model construction algorithm
and tool that tries to improve pHMM performance by using structural information
while training pHMMs. As a first step, HMMER-STRUCT constructs a set of pHMMs.
Each pHMM is constructed by weighting each residue in an aligned protein
according to a specific structural property of the residue. Properties used
were primary, secondary and tertiary structures, accessibility and packing.
HMMER-STRUCT then prioritizes the results by voting. Results: We used the SCOP
database to perform our experiments. Throughout, we apply leave-one-family-out
cross-validation over protein superfamilies. First, we used the MAMMOTH-mult
structural aligner to align the training set proteins. Then, we performed two
sets of experiments. In a first experiment, we compared structure weighted
models against standard pHMMs and against each other. In a second experiment,
we compared the voting model against individual pHMMs. We compare method
performance through ROC curves and through Precision/Recall curves, and assess
significance through the paired two tailed t-test. Our results show significant
performance improvements of all structurally weighted models over default
HMMER, and a significant improvement in sensitivity of the combined models over
both the original model and the structurally weighted models.
|
0704.2014
|
Extensive Games with Possibly Unaware Players
|
cs.GT cs.MA
|
Standard game theory assumes that the structure of the game is common
knowledge among players. We relax this assumption by considering extensive
games where agents may be unaware of the complete structure of the game. In
particular, they may not be aware of moves that they and other agents can make.
We show how such games can be represented; the key idea is to describe the game
from the point of view of every agent at every node of the game tree. We
provide a generalization of Nash equilibrium and show that every game with
awareness has a generalized Nash equilibrium. Finally, we extend these results
to games with awareness of unawareness, where a player i may be aware that a
player j can make moves that i is not aware of, and to subjective games, where
payers may have no common knowledge regarding the actual game and their beliefs
are incompatible with a common prior.
|
0704.2017
|
Large System Analysis of Game-Theoretic Power Control in UWB Wireless
Networks with Rake Receivers
|
cs.IT cs.GT math.IT
|
This paper studies the performance of partial-Rake (PRake) receivers in
impulse-radio ultrawideband wireless networks when an energy-efficient power
control scheme is adopted. Due to the large bandwidth of the system, the
multipath channel is assumed to be frequency-selective. By using noncooperative
game-theoretic models and large system analysis, explicit expressions are
derived in terms of network parameters to measure the effects of self- and
multiple-access interference at a receiving access point. Performance of the
PRake is compared in terms of achieved utilities and loss to that of the
all-Rake receiver.
|
0704.2083
|
Introduction to Arabic Speech Recognition Using CMUSphinx System
|
cs.CL cs.AI
|
In this paper Arabic was investigated from the speech recognition problem
point of view. We propose a novel approach to build an Arabic Automated Speech
Recognition System (ASR). This system is based on the open source CMU Sphinx-4,
from the Carnegie Mellon University. CMU Sphinx is a large-vocabulary;
speaker-independent, continuous speech recognition system based on discrete
Hidden Markov Models (HMMs). We build a model using utilities from the
OpenSource CMU Sphinx. We will demonstrate the possible adaptability of this
system to Arabic voice recognition.
|
0704.2092
|
A Note on the Inapproximability of Correlation Clustering
|
cs.LG cs.DS
|
We consider inapproximability of the correlation clustering problem defined
as follows: Given a graph $G = (V,E)$ where each edge is labeled either "+"
(similar) or "-" (dissimilar), correlation clustering seeks to partition the
vertices into clusters so that the number of pairs correctly (resp.
incorrectly) classified with respect to the labels is maximized (resp.
minimized). The two complementary problems are called MaxAgree and MinDisagree,
respectively, and have been studied on complete graphs, where every edge is
labeled, and general graphs, where some edge might not have been labeled.
Natural edge-weighted versions of both problems have been studied as well. Let
S-MaxAgree denote the weighted problem where all weights are taken from set S,
we show that S-MaxAgree with weights bounded by $O(|V|^{1/2-\delta})$
essentially belongs to the same hardness class in the following sense: if there
is a polynomial time algorithm that approximates S-MaxAgree within a factor of
$\lambda = O(\log{|V|})$ with high probability, then for any choice of S',
S'-MaxAgree can be approximated in polynomial time within a factor of $(\lambda
+ \epsilon)$, where $\epsilon > 0$ can be arbitrarily small, with high
probability. A similar statement also holds for $S-MinDisagree. This result
implies it is hard (assuming $NP \neq RP$) to approximate unweighted MaxAgree
within a factor of $80/79-\epsilon$, improving upon a previous known factor of
$116/115-\epsilon$ by Charikar et. al. \cite{Chari05}.
|
0704.2201
|
Arabic Speech Recognition System using CMU-Sphinx4
|
cs.CL cs.AI
|
In this paper we present the creation of an Arabic version of Automated
Speech Recognition System (ASR). This system is based on the open source
Sphinx-4, from the Carnegie Mellon University. Which is a speech recognition
system based on discrete hidden Markov models (HMMs). We investigate the
changes that must be made to the model to adapt Arabic voice recognition.
Keywords: Speech recognition, Acoustic model, Arabic language, HMMs,
CMUSphinx-4, Artificial intelligence.
|
0704.2258
|
On the Hardness of Approximating Stopping and Trapping Sets in LDPC
Codes
|
cs.IT math.IT
|
We prove that approximating the size of stopping and trapping sets in Tanner
graphs of linear block codes, and more restrictively, the class of low-density
parity-check (LDPC) codes, is NP-hard. The ramifications of our findings are
that methods used for estimating the height of the error-floor of moderate- and
long-length LDPC codes based on stopping and trapping set enumeration cannot
provide accurate worst-case performance predictions.
|
0704.2259
|
The Wiretap Channel with Feedback: Encryption over the Channel
|
cs.IT cs.CR math.IT
|
In this work, the critical role of noisy feedback in enhancing the secrecy
capacity of the wiretap channel is established. Unlike previous works, where a
noiseless public discussion channel is used for feedback, the feed-forward and
feedback signals share the same noisy channel in the present model. Quite
interestingly, this noisy feedback model is shown to be more advantageous in
the current setting. More specifically, the discrete memoryless modulo-additive
channel with a full-duplex destination node is considered first, and it is
shown that the judicious use of feedback increases the perfect secrecy capacity
to the capacity of the source-destination channel in the absence of the
wiretapper. In the achievability scheme, the feedback signal corresponds to a
private key, known only to the destination. In the half-duplex scheme, a novel
feedback technique that always achieves a positive perfect secrecy rate (even
when the source-wiretapper channel is less noisy than the source-destination
channel) is proposed. These results hinge on the modulo-additive property of
the channel, which is exploited by the destination to perform encryption over
the channel without revealing its key to the source. Finally, this scheme is
extended to the continuous real valued modulo-$\Lambda$ channel where it is
shown that the perfect secrecy capacity with feedback is also equal to the
capacity in the absence of the wiretapper.
|
0704.2353
|
Scaling Laws of Cognitive Networks
|
cs.IT math.IT
|
We consider a cognitive network consisting of n random pairs of cognitive
transmitters and receivers communicating simultaneously in the presence of
multiple primary users. Of interest is how the maximum throughput achieved by
the cognitive users scales with n. Furthermore, how far these users must be
from a primary user to guarantee a given primary outage. Two scenarios are
considered for the network scaling law: (i) when each cognitive transmitter
uses constant power to communicate with a cognitive receiver at a bounded
distance away, and (ii) when each cognitive transmitter scales its power
according to the distance to a considered primary user, allowing the cognitive
transmitter-receiver distances to grow. Using single-hop transmission, suitable
for cognitive devices of opportunistic nature, we show that, in both scenarios,
with path loss larger than 2, the cognitive network throughput scales linearly
with the number of cognitive users. We then explore the radius of a primary
exclusive region void of cognitive transmitters. We obtain bounds on this
radius for a given primary outage constraint. These bounds can help in the
design of a primary network with exclusive regions, outside of which cognitive
users may transmit freely. Our results show that opportunistic secondary
spectrum access using single-hop transmission is promising.
|
0704.2375
|
Power control algorithms for CDMA networks based on large system
analysis
|
cs.IT math.IT
|
Power control is a fundamental task accomplished in any wireless cellular
network; its aim is to set the transmit power of any mobile terminal, so that
each user is able to achieve its own target SINR. While conventional power
control algorithms require knowledge of a number of parameters of the signal of
interest and of the multiaccess interference, in this paper it is shown that in
a large CDMA system much of this information can be dispensed with, and
effective distributed power control algorithms may be implemented with very
little information on the user of interest. An uplink CDMA system subject to
flat fading is considered with a focus on the cases in which a linear MMSE
receiver and a non-linear MMSE serial interference cancellation receiver are
adopted; for the latter case new formulas are also given for the system SINR in
the large system asymptote. Experimental results show an excellent agreement
between the performance and the power profile of the proposed distributed
algorithms and that of conventional ones that require much greater prior
knowledge.
|
0704.2383
|
Power control and receiver design for energy efficiency in multipath
CDMA channels with bandlimited waveforms
|
cs.IT math.IT
|
This paper is focused on the cross-layer design problem of joint multiuser
detection and power control for energy-efficiency optimization in a wireless
data network through a game-theoretic approach. Building on work of Meshkati,
et al., wherein the tools of game-theory are used in order to achieve
energy-efficiency in a simple synchronous code division multiple access system,
system asynchronism, the use of bandlimited chip-pulses, and the multipath
distortion induced by the wireless channel are explicitly incorporated into the
analysis. Several non-cooperative games are proposed wherein users may vary
their transmit power and their uplink receiver in order to maximize their
utility, which is defined here as the ratio of data throughput to transmit
power. In particular, the case in which a linear multiuser detector is adopted
at the receiver is considered first, and then, the more challenging case in
which non-linear decision feedback multiuser detectors are employed is
considered. The proposed games are shown to admit a unique Nash equilibrium
point, while simulation results show the effectiveness of the proposed
solutions, as well as that the use of a decision-feedback multiuser receiver
brings remarkable performance improvements.
|
0704.2386
|
Bounded Pushdown dimension vs Lempel Ziv information density
|
cs.CC cs.IT math.IT
|
In this paper we introduce a variant of pushdown dimension called bounded
pushdown (BPD) dimension, that measures the density of information contained in
a sequence, relative to a BPD automata, i.e. a finite state machine equipped
with an extra infinite memory stack, with the additional requirement that every
input symbol only allows a bounded number of stack movements. BPD automata are
a natural real-time restriction of pushdown automata. We show that BPD
dimension is a robust notion by giving an equivalent characterization of BPD
dimension in terms of BPD compressors. We then study the relationships between
BPD compression, and the standard Lempel-Ziv (LZ) compression algorithm, and
show that in contrast to the finite-state compressor case, LZ is not universal
for bounded pushdown compressors in a strong sense: we construct a sequence
that LZ fails to compress signicantly, but that is compressed by at least a
factor 2 by a BPD compressor. As a corollary we obtain a strong separation
between finite-state and BPD dimension.
|
0704.2452
|
Optimum Linear LLR Calculation for Iterative Decoding on Fading Channels
|
cs.IT math.IT
|
On a fading channel with no channel state information at the receiver,
calculating true log-likelihood ratios (LLR) is complicated. Existing work
assume that the power of the additive noise is known and use the expected value
of the fading gain in a linear function of the channel output to find
approximate LLRs. In this work, we first assume that the power of the additive
noise is known and we find the optimum linear approximation of LLRs in the
sense of maximum achievable transmission rate on the channel. The maximum
achievable rate under this linear LLR calculation is almost equal to the
maximum achievable rate under true LLR calculation. We also observe that this
method appears to be the optimum in the sense of bit error rate performance
too. These results are then extended to the case that the noise power is
unknown at the receiver and a performance almost identical to the case that the
noise power is perfectly known is obtained.
|
0704.2475
|
Physical Layer Network Coding
|
cs.IT math.IT
|
A main distinguishing feature of a wireless network compared with a wired
network is its broadcast nature, in which the signal transmitted by a node may
reach several other nodes, and a node may receive signals from several other
nodes simultaneously. Rather than a blessing, this feature is treated more as
an interference-inducing nuisance in most wireless networks today (e.g., IEEE
802.11). This paper shows that the concept of network coding can be applied at
the physical layer to turn the broadcast property into a capacity-boosting
advantage in wireless ad hoc networks. Specifically, we propose a
physical-layer network coding (PNC) scheme to coordinate transmissions among
nodes. In contrast to straightforward network coding which performs coding
arithmetic on digital bit streams after they have been received, PNC makes use
of the additive nature of simultaneously arriving electromagnetic (EM) waves
for equivalent coding operation. And in doing so, PNC can potentially achieve
100% and 50% throughput increases compared with traditional transmission and
straightforward network coding, respectively, in multi-hop networks. More
specifically, the information-theoretic capacity of PNC is almost double that
of traditional transmission in the SNR region of practical interest (higher
than 0dB). We believe this is a first paper that ventures into EM-wave-based
network coding at the physical layer and demonstrates its potential for
boosting network capacity.
|
0704.2505
|
Algebraic Distributed Space-Time Codes with Low ML Decoding Complexity
|
cs.IT cs.DM math.IT
|
"Extended Clifford algebras" are introduced as a means to obtain low ML
decoding complexity space-time block codes. Using left regular matrix
representations of two specific classes of extended Clifford algebras, two
systematic algebraic constructions of full diversity Distributed Space-Time
Codes (DSTCs) are provided for any power of two number of relays. The left
regular matrix representation has been shown to naturally result in space-time
codes meeting the additional constraints required for DSTCs. The DSTCs so
constructed have the salient feature of reduced Maximum Likelihood (ML)
decoding complexity. In particular, the ML decoding of these codes can be
performed by applying the lattice decoder algorithm on a lattice of four times
lesser dimension than what is required in general. Moreover these codes have a
uniform distribution of power among the relays and in time, thus leading to a
low Peak to Average Power Ratio at the relays.
|
0704.2507
|
STBCs from Representation of Extended Clifford Algebras
|
cs.IT cs.DM math.IT
|
A set of sufficient conditions to construct $\lambda$-real symbol Maximum
Likelihood (ML) decodable STBCs have recently been provided by Karmakar et al.
STBCs satisfying these sufficient conditions were named as Clifford Unitary
Weight (CUW) codes. In this paper, the maximal rate (as measured in complex
symbols per channel use) of CUW codes for $\lambda=2^a,a\in\mathbb{N}$ is
obtained using tools from representation theory. Two algebraic constructions of
codes achieving this maximal rate are also provided. One of the constructions
is obtained using linear representation of finite groups whereas the other
construction is based on the concept of right module algebra over
non-commutative rings. To the knowledge of the authors, this is the first paper
in which matrices over non-commutative rings is used to construct STBCs. An
algebraic explanation is provided for the 'ABBA' construction first proposed by
Tirkkonen et al and the tensor product construction proposed by Karmakar et al.
Furthermore, it is established that the 4 transmit antenna STBC originally
proposed by Tirkkonen et al based on the ABBA construction is actually a single
complex symbol ML decodable code if the design variables are permuted and
signal sets of appropriate dimensions are chosen.
|
0704.2509
|
Signal Set Design for Full-Diversity Low-Decoding-Complexity
Differential Scaled-Unitary STBCs
|
cs.IT math.IT
|
The problem of designing high rate, full diversity noncoherent space-time
block codes (STBCs) with low encoding and decoding complexity is addressed.
First, the notion of $g$-group encodable and $g$-group decodable linear STBCs
is introduced. Then for a known class of rate-1 linear designs, an explicit
construction of fully-diverse signal sets that lead to four-group encodable and
four-group decodable differential scaled unitary STBCs for any power of two
number of antennas is provided. Previous works on differential STBCs either
sacrifice decoding complexity for higher rate or sacrifice rate for lower
decoding complexity.
|
0704.2511
|
Noncoherent Low-Decoding-Complexity Space-Time Codes for Wireless Relay
Networks
|
cs.IT math.IT
|
The differential encoding/decoding setup introduced by Kiran et al, Oggier et
al and Jing et al for wireless relay networks that use codebooks consisting of
unitary matrices is extended to allow codebooks consisting of scaled unitary
matrices. For such codebooks to be used in the Jing-Hassibi protocol for
cooperative diversity, the conditions that need to be satisfied by the relay
matrices and the codebook are identified. A class of previously known rate one,
full diversity, four-group encodable and four-group decodable Differential
Space-Time Codes (DSTCs) is proposed for use as Distributed DSTCs (DDSTCs) in
the proposed set up. To the best of our knowledge, this is the first known low
decoding complexity DDSTC scheme for cooperative wireless networks.
|
0704.2544
|
Existence Proofs of Some EXIT Like Functions
|
cs.IT math.IT
|
The Extended BP (EBP) Generalized EXIT (GEXIT) function introduced in
\cite{MMRU05} plays a fundamental role in the asymptotic analysis of sparse
graph codes. For transmission over the binary erasure channel (BEC) the
analytic properties of the EBP GEXIT function are relatively simple and well
understood. The general case is much harder and even the existence of the curve
is not known in general. We introduce some tools from non-linear analysis which
can be useful to prove the existence of EXIT like curves in some cases. The
main tool is the Krasnoselskii-Rabinowitz (KR) bifurcation theorem.
|
0704.2596
|
Computing Extensions of Linear Codes
|
cs.IT cs.DM math.IT
|
This paper deals with the problem of increasing the minimum distance of a
linear code by adding one or more columns to the generator matrix. Several
methods to compute extensions of linear codes are presented. Many codes
improving the previously known lower bounds on the minimum distance have been
found.
|
0704.2644
|
Joint universal lossy coding and identification of stationary mixing
sources
|
cs.IT cs.LG math.IT
|
The problem of joint universal source coding and modeling, treated in the
context of lossless codes by Rissanen, was recently generalized to fixed-rate
lossy coding of finitely parametrized continuous-alphabet i.i.d. sources. We
extend these results to variable-rate lossy block coding of stationary ergodic
sources and show that, for bounded metric distortion measures, any finitely
parametrized family of stationary sources satisfying suitable mixing,
smoothness and Vapnik-Chervonenkis learnability conditions admits universal
schemes for joint lossy source coding and identification. We also give several
explicit examples of parametric sources satisfying the regularity conditions.
|
0704.2651
|
Opportunistic Communications in an Orthogonal Multiaccess Relay Channel
|
cs.IT math.IT
|
The problem of resource allocation is studied for a two-user fading
orthogonal multiaccess relay channel (MARC) where both users (sources)
communicate with a destination in the presence of a relay. A half-duplex relay
is considered that transmits on a channel orthogonal to that used by the
sources. The instantaneous fading state between every transmit-receive pair in
this network is assumed to be known at both the transmitter and receiver. Under
an average power constraint at each source and the relay, the sum-rate for the
achievable strategy of decode-and-forward (DF) is maximized over all power
allocations (policies) at the sources and relay. It is shown that the sum-rate
maximizing policy exploits the multiuser fading diversity to reveal the
optimality of opportunistic channel use by each user. A geometric
interpretation of the optimal power policy is also presented.
|
0704.2659
|
Minimum Expected Distortion in Gaussian Layered Broadcast Coding with
Successive Refinement
|
cs.IT math.IT
|
A transmitter without channel state information (CSI) wishes to send a
delay-limited Gaussian source over a slowly fading channel. The source is coded
in superimposed layers, with each layer successively refining the description
in the previous one. The receiver decodes the layers that are supported by the
channel realization and reconstructs the source up to a distortion. In the
limit of a continuum of infinite layers, the optimal power distribution that
minimizes the expected distortion is given by the solution to a set of linear
differential equations in terms of the density of the fading distribution. In
the optimal power distribution, as SNR increases, the allocation over the
higher layers remains unchanged; rather the extra power is allocated towards
the lower layers. On the other hand, as the bandwidth ratio b (channel uses per
source symbol) tends to zero, the power distribution that minimizes expected
distortion converges to the power distribution that maximizes expected
capacity. While expected distortion can be improved by acquiring CSI at the
transmitter (CSIT) or by increasing diversity from the realization of
independent fading paths, at high SNR the performance benefit from diversity
exceeds that from CSIT, especially when b is large.
|
0704.2668
|
Supervised Feature Selection via Dependence Estimation
|
cs.LG
|
We introduce a framework for filtering features that employs the
Hilbert-Schmidt Independence Criterion (HSIC) as a measure of dependence
between the features and the labels. The key idea is that good features should
maximise such dependence. Feature selection for various supervised learning
problems (including classification and regression) is unified under this
framework, and the solutions can be approximated using a backward-elimination
algorithm. We demonstrate the usefulness of our method on both artificial and
real world datasets.
|
0704.2680
|
A Channel that Heats Up
|
cs.IT math.IT
|
Motivated by on-chip communication, a channel model is proposed where the
variance of the additive noise depends on the weighted sum of the past channel
input powers. For this channel, an expression for the capacity per unit cost is
derived, and it is shown that the expression holds also in the presence of
feedback.
|
0704.2725
|
Exploiting Heavy Tails in Training Times of Multilayer Perceptrons: A
Case Study with the UCI Thyroid Disease Database
|
cs.NE
|
The random initialization of weights of a multilayer perceptron makes it
possible to model its training process as a Las Vegas algorithm, i.e. a
randomized algorithm which stops when some required training error is obtained,
and whose execution time is a random variable. This modeling is used to perform
a case study on a well-known pattern recognition benchmark: the UCI Thyroid
Disease Database. Empirical evidence is presented of the training time
probability distribution exhibiting a heavy tail behavior, meaning a big
probability mass of long executions. This fact is exploited to reduce the
training time cost by applying two simple restart strategies. The first assumes
full knowledge of the distribution yielding a 40% cut down in expected time
with respect to the training without restarts. The second, assumes null
knowledge, yielding a reduction ranging from 9% to 23%.
|
0704.2778
|
Random Access Broadcast: Stability and Throughput Analysis
|
cs.IT math.IT
|
A wireless network in which packets are broadcast to a group of receivers
through use of a random access protocol is considered in this work. The
relation to previous work on networks of interacting queues is discussed and
subsequently, the stability and throughput regions of the system are analyzed
and presented. A simple network of two source nodes and two destination nodes
is considered first. The broadcast service process is analyzed assuming a
channel that allows for packet capture and multipacket reception. In this small
network, the stability and throughput regions are observed to coincide. The
same problem for a network with N sources and M destinations is considered
next. The channel model is simplified in that multipacket reception is no
longer permitted. Bounds on the stability region are developed using the
concept of stability rank and the throughput region of the system is compared
to the bounds. Our results show that as the number of destination nodes
increases, the stability and throughput regions diminish. Additionally, a
previous conjecture that the stability and throughput regions coincide for a
network of arbitrarily many sources is supported for a broadcast scenario by
the results presented in this work.
|
0704.2786
|
Writing on Dirty Paper with Resizing and its Application to Quasi-Static
Fading Broadcast Channels
|
cs.IT math.IT
|
This paper studies a variant of the classical problem of ``writing on dirty
paper'' in which the sum of the input and the interference, or dirt, is
multiplied by a random variable that models resizing, known to the decoder but
not to the encoder. The achievable rate of Costa's dirty paper coding (DPC)
scheme is calculated and compared to the case of the decoder's also knowing the
dirt. In the ergodic case, the corresponding rate loss vanishes asymptotically
in the limits of both high and low signal-to-noise ratio (SNR), and is small at
all finite SNR for typical distributions like Rayleigh, Rician, and Nakagami.
In the quasi-static case, the DPC scheme is lossless at all SNR in terms of
outage probability. Quasi-static fading broadcast channels (BC) without
transmit channel state information (CSI) are investigated as an application of
the robustness properties. It is shown that the DPC scheme leads to an outage
achievable rate region that strictly dominates that of time division.
|
0704.2808
|
Minimum cost distributed source coding over a network
|
cs.IT cs.NI math.IT
|
This work considers the problem of transmitting multiple compressible sources
over a network at minimum cost. The aim is to find the optimal rates at which
the sources should be compressed and the network flows using which they should
be transmitted so that the cost of the transmission is minimal. We consider
networks with capacity constraints and linear cost functions. The problem is
complicated by the fact that the description of the feasible rate region of
distributed source coding problems typically has a number of constraints that
is exponential in the number of sources. This renders general purpose solvers
inefficient. We present a framework in which these problems can be solved
efficiently by exploiting the structure of the feasible rate regions coupled
with dual decomposition and optimization techniques such as the subgradient
method and the proximal bundle method.
|
0704.2811
|
On Algebraic Decoding of $q$-ary Reed-Muller and Product-Reed-Solomon
Codes
|
cs.IT cs.DM math.IT
|
We consider a list decoding algorithm recently proposed by Pellikaan-Wu
\cite{PW2005} for $q$-ary Reed-Muller codes $\mathcal{RM}_q(\ell, m, n)$ of
length $n \leq q^m$ when $\ell \leq q$. A simple and easily accessible
correctness proof is given which shows that this algorithm achieves a relative
error-correction radius of $\tau \leq (1 - \sqrt{{\ell q^{m-1}}/{n}})$. This is
an improvement over the proof using one-point Algebraic-Geometric codes given
in \cite{PW2005}. The described algorithm can be adapted to decode
Product-Reed-Solomon codes.
We then propose a new low complexity recursive algebraic decoding algorithm
for Reed-Muller and Product-Reed-Solomon codes. Our algorithm achieves a
relative error correction radius of $\tau \leq \prod_{i=1}^m (1 -
\sqrt{k_i/q})$. This technique is then proved to outperform the Pellikaan-Wu
method in both complexity and error correction radius over a wide range of code
rates.
|
0704.2841
|
A High-Throughput Cross-Layer Scheme for Distributed Wireless Ad Hoc
Networks
|
cs.IT math.IT
|
In wireless ad hoc networks, distributed nodes can collaboratively form an
antenna array for long-distance communications to achieve high energy
efficiency. In recent work, Ochiai, et al., have shown that such collaborative
beamforming can achieve a statistically nice beampattern with a narrow main
lobe and low sidelobes. However, the process of collaboration introduces
significant delay, since all collaborating nodes need access to the same
information. In this paper, a technique that significantly reduces the
collaboration overhead is proposed. It consists of two phases. In the first
phase, nodes transmit locally in a random access fashion. Collisions, when they
occur, are viewed as linear mixtures of the collided packets. In the second
phase, a set of cooperating nodes acts as a distributed antenna system and
beamform the received analog waveform to one or more faraway destinations. This
step requires multiplication of the received analog waveform by a complex
number, which is independently computed by each cooperating node, and which
enables separation of the collided packets based on their final destination.
The scheme requires that each node has global knowledge of the network
coordinates. The proposed scheme can achieve high throughput, which in certain
cases exceeds one.
|
0704.2857
|
Modern Coding Theory: The Statistical Mechanics and Computer Science
Point of View
|
cs.IT cond-mat.stat-mech math.IT
|
These are the notes for a set of lectures delivered by the two authors at the
Les Houches Summer School on `Complex Systems' in July 2006. They provide an
introduction to the basic concepts in modern (probabilistic) coding theory,
highlighting connections with statistical mechanics. We also stress common
concepts with other disciplines dealing with similar problems that can be
generically referred to as `large graphical models'.
While most of the lectures are devoted to the classical channel coding
problem over simple memoryless channels, we present a discussion of more
complex channel models. We conclude with an overview of the main open
challenges in the field.
|
0704.2902
|
Recommending Related Papers Based on Digital Library Access Records
|
cs.DL cs.IR
|
An important goal for digital libraries is to enable researchers to more
easily explore related work. While citation data is often used as an indicator
of relatedness, in this paper we demonstrate that digital access records (e.g.
http-server logs) can be used as indicators as well. In particular, we show
that measures based on co-access provide better coverage than co-citation, that
they are available much sooner, and that they are more accurate for recent
papers.
|
0704.2926
|
Optimal Routing for the Gaussian Multiple-Relay Channel with
Decode-and-Forward
|
cs.IT math.IT
|
In this paper, we study a routing problem on the Gaussian multiple relay
channel, in which nodes employ a decode-and-forward coding strategy. We are
interested in routes for the information flow through the relays that achieve
the highest DF rate. We first construct an algorithm that provably finds
optimal DF routes. As the algorithm runs in factorial time in the worst case,
we propose a polynomial time heuristic algorithm that finds an optimal route
with high probability. We demonstrate that that the optimal (and near optimal)
DF routes are good in practice by simulating a distributed DF coding scheme
using low density parity check codes with puncturing and incremental
redundancy.
|
0704.2963
|
Using Access Data for Paper Recommendations on ArXiv.org
|
cs.DL cs.IR
|
This thesis investigates in the use of access log data as a source of
information for identifying related scientific papers. This is done for
arXiv.org, the authority for publication of e-prints in several fields of
physics.
Compared to citation information, access logs have the advantage of being
immediately available, without manual or automatic extraction of the citation
graph. Because of that, a main focus is on the question, how far user behavior
can serve as a replacement for explicit meta-data, which potentially might be
expensive or completely unavailable. Therefore, we compare access, content, and
citation-based measures of relatedness on different recommendation tasks. As a
final result, an online recommendation system has been built that can help
scientists to find further relevant literature, without having to search for
them actively.
|
0704.3019
|
Arbitrary Rate Permutation Modulation for the Gaussian Channel
|
cs.IT math.IT
|
In this paper non-group permutation modulated sequences for the Gaussian
channel are considered. Without the restriction to group codes rather than
subsets of group codes, arbitrary rates are achievable. The code construction
utilizes the known optimal group constellations to ensure at least the same
performance but exploit the Gray code ordering structure of multiset
permutations as a selection criterion at the decoder. The decoder achieves near
maximum likelihood performance at low computational cost and low additional
memory requirements at the receiver.
|
0704.3035
|
Achievable Rates for Two-Way Wire-Tap Channels
|
cs.IT cs.CR math.IT
|
We consider two-way wire-tap channels, where two users are communicating with
each other in the presence of an eavesdropper, who has access to the
communications through a multiple-access channel. We find achievable rates for
two different scenarios, the Gaussian two-way wire-tap channel, (GTW-WT), and
the binary additive two-way wire-tap channel, (BATW-WT). It is shown that the
two-way channels inherently provide a unique advantage for wire-tapped
scenarios, as the users know their own transmitted signals and in effect help
encrypt the other user's messages, similar to a one-time pad. We compare the
achievable rates to that of the Gaussian multiple-access wire-tap channel
(GMAC-WT) to illustrate this advantage.
|
0704.3094
|
Detection of two-sided alternatives in a Brownian motion model
|
cs.IT math.IT
|
This work examines the problem of sequential detection of a change in the
drift of a Brownian motion in the case of two-sided alternatives. Applications
to real life situations in which two-sided changes can occur are discussed.
Traditionally, 2-CUSUM stopping rules have been used for this problem due to
their asymptotically optimal character as the mean time between false alarms
tends to $\infty$. In particular, attention has focused on 2-CUSUM harmonic
mean rules due to the simplicity in calculating their first moments. In this
paper, we derive closed-form expressions for the first moment of a general
2-CUSUM stopping rule. We use these expressions to obtain explicit upper and
lower bounds for it. Moreover, we derive an expression for the rate of change
of this first moment as one of the threshold parameters changes. Based on these
expressions we obtain explicit upper and lower bounds to this rate of change.
Using these expressions we are able to find the best 2-CUSUM stopping rule with
respect to the extended Lorden criterion. In fact, we demonstrate not only the
existence but also the uniqueness of the best 2-CUSUM stopping both in the case
of a symmetric change and in the case of a non-symmetric case. Furthermore, we
discuss the existence of a modification of the 2-CUSUM stopping rule that has a
strictly better performance than its classical 2-CUSUM counterpart for small
values of the mean time between false alarms. We conclude with a discussion on
the open problem of strict optimality in the case of two-sided alternatives.
|
0704.3120
|
Space Time Codes from Permutation Codes
|
cs.IT math.IT
|
A new class of space time codes with high performance is presented. The code
design utilizes tailor-made permutation codes, which are known to have large
minimal distances as spherical codes. A geometric connection between spherical
and space time codes has been used to translate them into the final space time
codes. Simulations demonstrate that the performance increases with the block
lengths, a result that has been conjectured already in previous work. Further,
the connection to permutation codes allows for moderate complex en-/decoding
algorithms.
|
0704.3157
|
Experimenting with recursive queries in database and logic programming
systems
|
cs.AI cs.DB
|
This paper considers the problem of reasoning on massive amounts of (possibly
distributed) data. Presently, existing proposals show some limitations: {\em
(i)} the quantity of data that can be handled contemporarily is limited, due to
the fact that reasoning is generally carried out in main-memory; {\em (ii)} the
interaction with external (and independent) DBMSs is not trivial and, in
several cases, not allowed at all; {\em (iii)} the efficiency of present
implementations is still not sufficient for their utilization in complex
reasoning tasks involving massive amounts of data. This paper provides a
contribution in this setting; it presents a new system, called DLV$^{DB}$,
which aims to solve these problems. Moreover, the paper reports the results of
a thorough experimental analysis we have carried out for comparing our system
with several state-of-the-art systems (both logic and databases) on some
classical deductive problems; the other tested systems are: LDL++, XSB, Smodels
and three top-level commercial DBMSs. DLV$^{DB}$ significantly outperforms even
the commercial Database Systems on recursive queries. To appear in Theory and
Practice of Logic Programming (TPLP)
|
0704.3199
|
Generalized Stability Condition for Generalized and Doubly-Generalized
LDPC Codes
|
cs.IT math.IT
|
In this paper, the stability condition for low-density parity-check (LDPC)
codes on the binary erasure channel (BEC) is extended to generalized LDPC
(GLDPC) codes and doublygeneralized LDPC (D-GLDPC) codes. It is proved that, in
both cases, the stability condition only involves the component codes with
minimum distance 2. The stability condition for GLDPC codes is always expressed
as an upper bound to the decoding threshold. This is not possible for D-GLDPC
codes, unless all the generalized variable nodes have minimum distance at least
3. Furthermore, a condition called derivative matching is defined in the paper.
This condition is sufficient for a GLDPC or DGLDPC code to achieve the
stability condition with equality. If this condition is satisfied, the
threshold of D-GLDPC codes (whose generalized variable nodes have all minimum
distance at least 3) and GLDPC codes can be expressed in closed form.
|
0704.3241
|
Neighbor Discovery in Wireless Networks:A Multiuser-Detection Approach
|
cs.IT math.IT
|
We examine the problem of determining which nodes are neighbors of a given
one in a wireless network. We consider an unsupervised network operating on a
frequency-flat Gaussian channel, where $K+1$ nodes associate their identities
to nonorthogonal signatures, transmitted at random times, synchronously, and
independently. A number of neighbor-discovery algorithms, based on different
optimization criteria, are introduced and analyzed. Numerical results show how
reduced-complexity algorithms can achieve a satisfactory performance.
|
0704.3268
|
2D Path Solutions from a Single Layer Excitable CNN Model
|
cs.RO cs.NE
|
An easily implementable path solution algorithm for 2D spatial problems,
based on excitable/programmable characteristics of a specific cellular
nonlinear network (CNN) model is presented and numerically investigated. The
network is a single layer bioinspired model which was also implemented in CMOS
technology. It exhibits excitable characteristics with regionally bistable
cells. The related response realizes propagations of trigger autowaves, where
the excitable mode can be globally preset and reset. It is shown that, obstacle
distributions in 2D space can also be directly mapped onto the coupled cell
array in the network. Combining these two features, the network model can serve
as the main block in a 2D path computing processor. The related algorithm and
configurations are numerically experimented with circuit level parameters and
performance estimations are also presented. The simplicity of the model also
allows alternative technology and device level implementation, which may become
critical in autonomous processor design of related micro or nanoscale robotic
applications.
|
0704.3287
|
Sample size cognizant detection of signals in white noise
|
cs.IT math.IT
|
The detection and estimation of signals in noisy, limited data is a problem
of interest to many scientific and engineering communities. We present a
computationally simple, sample eigenvalue based procedure for estimating the
number of high-dimensional signals in white noise when there are relatively few
samples. We highlight a fundamental asymptotic limit of sample eigenvalue based
detection of weak high-dimensional signals from a limited sample size and
discuss its implication for the detection of two closely spaced signals.
This motivates our heuristic definition of the 'effective number of
identifiable signals.' Numerical simulations are used to demonstrate the
consistency of the algorithm with respect to the effective number of signals
and the superior performance of the algorithm with respect to Wax and Kailath's
"asymptotically consistent" MDL based estimator.
|
0704.3292
|
Coalition Games with Cooperative Transmission: A Cure for the Curse of
Boundary Nodes in Selfish Packet-Forwarding Wireless Networks
|
cs.IT math.IT
|
In wireless packet-forwarding networks with selfish nodes, applications of a
repeated game can induce the nodes to forward each others' packets, so that the
network performance can be improved. However, the nodes on the boundary of such
networks cannot benefit from this strategy, as the other nodes do not depend on
them. This problem is sometimes known as the curse of the boundary nodes. To
overcome this problem, an approach based on coalition games is proposed, in
which the boundary nodes can use cooperative transmission to help the backbone
nodes in the middle of the network. In return, the backbone nodes are willing
to forward the boundary nodes' packets. The stability of the coalitions is
studied using the concept of a core. Then two types of fairness, namely, the
min-max fairness using nucleolus and the average fairness using the Shapley
function are investigated. Finally, a protocol is designed using both repeated
games and coalition games. Simulation results show how boundary nodes and
backbone nodes form coalitions together according to different fairness
criteria. The proposed protocol can improve the network connectivity by about
50%, compared with pure repeated game schemes.
|
0704.3316
|
Vocabulary growth in collaborative tagging systems
|
cs.IR cond-mat.stat-mech cs.CY physics.data-an
|
We analyze a large-scale snapshot of del.icio.us and investigate how the
number of different tags in the system grows as a function of a suitably
defined notion of time. We study the temporal evolution of the global
vocabulary size, i.e. the number of distinct tags in the entire system, as well
as the evolution of local vocabularies, that is the growth of the number of
distinct tags used in the context of a given resource or user. In both cases,
we find power-law behaviors with exponents smaller than one. Surprisingly, the
observed growth behaviors are remarkably regular throughout the entire history
of the system and across very different resources being bookmarked. Similar
sub-linear laws of growth have been observed in written text, and this
qualitative universality calls for an explanation and points in the direction
of non-trivial cognitive processes in the complex interaction patterns
characterizing collaborative tagging.
|
0704.3359
|
Direct Optimization of Ranking Measures
|
cs.IR cs.AI
|
Web page ranking and collaborative filtering require the optimization of
sophisticated performance measures. Current Support Vector approaches are
unable to optimize them directly and focus on pairwise comparisons instead. We
present a new approach which allows direct optimization of the relevant loss
functions. This is achieved via structured estimation in Hilbert spaces. It is
most related to Max-Margin-Markov networks optimization of multivariate
performance measures. Key to our approach is that during training the ranking
problem can be viewed as a linear assignment problem, which can be solved by
the Hungarian Marriage algorithm. At test time, a sort operation is sufficient,
as our algorithm assigns a relevance score to every (document, query) pair.
Experiments show that the our algorithm is fast and that it works very well.
|
0704.3391
|
Lifetime Improvement in Wireless Sensor Networks via Collaborative
Beamforming and Cooperative Transmission
|
cs.IT math.IT
|
Collaborative beamforming (CB) and cooperative transmission (CT) have
recently emerged as communication techniques that can make effective use of
collaborative/cooperative nodes to create a virtual
multiple-input/multiple-output (MIMO) system. Extending the lifetime of
networks composed of battery-operated nodes is a key issue in the design and
operation of wireless sensor networks. This paper considers the effects on
network lifetime of allowing closely located nodes to use CB/CT to reduce the
load or even to avoid packet-forwarding requests to nodes that have critical
battery life. First, the effectiveness of CB/CT in improving the signal
strength at a faraway destination using energy in nearby nodes is studied.
Then, the performance improvement obtained by this technique is analyzed for a
special 2D disk case. Further, for general networks in which
information-generation rates are fixed, a new routing problem is formulated as
a linear programming problem, while for other general networks, the cost for
routing is dynamically adjusted according to the amount of energy remaining and
the effectiveness of CB/CT. From the analysis and the simulation results, it is
seen that the proposed method can reduce the payloads of energy-depleting nodes
by about 90% in the special case network considered and improve the lifetimes
of general networks by about 10%, compared with existing techniques.
|
0704.3395
|
General-Purpose Computing on a Semantic Network Substrate
|
cs.AI cs.PL
|
This article presents a model of general-purpose computing on a semantic
network substrate. The concepts presented are applicable to any semantic
network representation. However, due to the standards and technological
infrastructure devoted to the Semantic Web effort, this article is presented
from this point of view. In the proposed model of computing, the application
programming interface, the run-time program, and the state of the computing
virtual machine are all represented in the Resource Description Framework
(RDF). The implementation of the concepts presented provides a practical
computing paradigm that leverages the highly-distributed and standardized
representational-layer of the Semantic Web.
|
0704.3396
|
Lifetime Improvement of Wireless Sensor Networks by Collaborative
Beamforming and Cooperative Transmission
|
cs.IT math.IT
|
Extending network lifetime of battery-operated devices is a key design issue
that allows uninterrupted information exchange among distributive nodes in
wireless sensor networks. Collaborative beamforming (CB) and cooperative
transmission (CT) have recently emerged as new communication techniques that
enable and leverage effective resource sharing among collaborative/cooperative
nodes. In this paper, we seek to maximize the lifetime of sensor networks by
using the new idea that closely located nodes can use CB/CT to reduce the load
or even avoid packet forwarding requests to nodes that have critical battery
life. First, we study the effectiveness of CB/CT to improve the signal strength
at a faraway destination using energy in nearby nodes. Then, a 2D disk case is
analyzed to assess the resulting performance improvement. For general networks,
if information-generation rates are fixed, the new routing problem is
formulated as a linear programming problem; otherwise, the cost for routing is
dynamically adjusted according to the amount of energy remaining and the
effectiveness of CB/CT. From the analysis and simulation results, it is seen
that the proposed schemes can improve the lifetime by about 90% in the 2D disk
network and by about 10% in the general networks, compared to existing schemes.
|
0704.3399
|
Cooperative Transmission Protocols with High Spectral Efficiency and
High Diversity Order Using Multiuser Detection and Network Coding
|
cs.IT math.IT
|
Cooperative transmission is an emerging communication technique that takes
advantages of the broadcast nature of wireless channels. However, due to low
spectral efficiency and the requirement of orthogonal channels, its potential
for use in future wireless networks is limited. In this paper, by making use of
multiuser detection (MUD) and network coding, cooperative transmission
protocols with high spectral efficiency, diversity order, and coding gain are
developed. Compared with the traditional cooperative transmission protocols
with single-user detection, in which the diversity gain is only for one source
user, the proposed MUD cooperative transmission protocols have the merits that
the improvement of one user's link can also benefit the other users. In
addition, using MUD at the relay provides an environment in which network
coding can be employed. The coding gain and high diversity order can be
obtained by fully utilizing the link between the relay and the destination.
From the analysis and simulation results, it is seen that the proposed
protocols achieve higher diversity gain, better asymptotic efficiency, and
lower bit error rate, compared to traditional MUD and to existing cooperative
transmission protocols.
|
0704.3402
|
Diversity-Multiplexing Tradeoff in Selective-Fading MIMO Channels
|
cs.IT math.IT
|
We establish the optimal diversity-multiplexing (DM) tradeoff of coherent
time, frequency and time-frequency selective-fading MIMO channels and provide a
code design criterion for DM-tradeoff optimality. Our results are based on the
analysis of the "Jensen channel" associated to a given selective-fading MIMO
channel. While the original problem seems analytically intractable due to the
mutual information being a sum of correlated random variables, the Jensen
channel is equivalent to the original channel in the sense of the DM-tradeoff
and lends itself nicely to analytical treatment. Finally, as a consequence of
our results, we find that the classical rank criterion for space-time code
design (in selective-fading MIMO channels) ensures optimality in the sense of
the DM-tradeoff.
|
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