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0709.4506
|
Optimum Diversity-Multiplexing Tradeoff in the Multiple Relays Network
|
cs.IT math.IT
|
In this paper, a multiple-relay network in considered, in which $K$
single-antenna relays assist a single-antenna transmitter to communicate with a
single-antenna receiver in a half-duplex mode. A new Amplify and Forward (AF)
scheme is proposed for this network and is shown to achieve the optimum
diversity-multiplexing trade-off curve.
|
0709.4513
|
Scheduling and Pre-Conditioning in Multi-User MIMO TDD Systems
|
cs.IT math.IT
|
The downlink transmission in multi-user multiple-input multiple-output (MIMO)
systems has been extensively studied from both communication-theoretic and
information-theoretic perspectives. Most of these papers assume
perfect/imperfect channel knowledge. In general, the problem of channel
training and estimation is studied separately. However, in interference-limited
communication systems with high mobility, this problem is tightly coupled with
the problem of maximizing throughput of the system. In this paper, scheduling
and pre-conditioning based schemes in the presence of reciprocal channel are
considered to address this. In the case of homogeneous users, a scheduling
scheme is proposed and an improved lower bound on the sum capacity is derived.
The problem of choosing training sequence length to maximize net throughput of
the system is studied. In the case of heterogeneous users, a modified
pre-conditioning method is proposed and an optimized pre-conditioning matrix is
derived. This method is combined with a scheduling scheme to further improve
net achievable weighted-sum rate.
|
0709.4655
|
Mining for trees in a graph is NP-complete
|
cs.DB cs.AI
|
Mining for trees in a graph is shown to be NP-complete.
|
0709.4669
|
The Extended Edit Distance Metric
|
cs.IR
|
Similarity search is an important problem in information retrieval. This
similarity is based on a distance. Symbolic representation of time series has
attracted many researchers recently, since it reduces the dimensionality of
these high dimensional data objects. We propose a new distance metric that is
applied to symbolic data objects and we test it on time series data bases in a
classification task. We compare it to other distances that are well known in
the literature for symbolic data objects. We also prove, mathematically, that
our distance is metric.
|
0709.4671
|
Secrecy Capacity Region of a Multi-Antenna Gaussian Broadcast Channel
with Confidential Messages
|
cs.IT math.IT
|
In wireless data networks, communication is particularly susceptible to
eavesdropping due to its broadcast nature. Security and privacy systems have
become critical for wireless providers and enterprise networks. This paper
considers the problem of secret communication over the Gaussian broadcast
channel, where a multi-antenna transmitter sends independent confidential
messages to two users with information-theoretic secrecy. That is, each user
would like to obtain its own confidential message in a reliable and safe
manner. This communication model is referred to as the multi-antenna Gaussian
broadcast channel with confidential messages (MGBC-CM). Under this
communication scenario, a secret dirty-paper coding scheme and the
corresponding achievable secrecy rate region are first developed based on
Gaussian codebooks. Next, a computable Sato-type outer bound on the secrecy
capacity region is provided for the MGBC-CM. Furthermore, the Sato-type outer
bound prove to be consistent with the boundary of the secret dirty-paper coding
achievable rate region, and hence, the secrecy capacity region of the MGBC-CM
is established. Finally, two numerical examples demonstrate that both users can
achieve positive rates simultaneously under the information-theoretic secrecy
requirement.
|
0710.0009
|
Bio-linguistic transition and Baldwin effect in an evolutionary
naming-game model
|
cs.CL cond-mat.stat-mech cs.AI physics.soc-ph q-bio.PE
|
We examine an evolutionary naming-game model where communicating agents are
equipped with an evolutionarily selected learning ability. Such a coupling of
biological and linguistic ingredients results in an abrupt transition: upon a
small change of a model control parameter a poorly communicating group of
linguistically unskilled agents transforms into almost perfectly communicating
group with large learning abilities. When learning ability is kept fixed, the
transition appears to be continuous. Genetic imprinting of the learning
abilities proceeds via Baldwin effect: initially unskilled communicating agents
learn a language and that creates a niche in which there is an evolutionary
pressure for the increase of learning ability.Our model suggests that when
linguistic (or cultural) processes became intensive enough, a transition took
place where both linguistic performance and biological endowment of our species
experienced an abrupt change that perhaps triggered the rapid expansion of
human civilization.
|
0710.0013
|
Lagrangian Relaxation for MAP Estimation in Graphical Models
|
cs.AI
|
We develop a general framework for MAP estimation in discrete and Gaussian
graphical models using Lagrangian relaxation techniques. The key idea is to
reformulate an intractable estimation problem as one defined on a more
tractable graph, but subject to additional constraints. Relaxing these
constraints gives a tractable dual problem, one defined by a thin graph, which
is then optimized by an iterative procedure. When this iterative optimization
leads to a consistent estimate, one which also satisfies the constraints, then
it corresponds to an optimal MAP estimate of the original model. Otherwise
there is a ``duality gap'', and we obtain a bound on the optimal solution.
Thus, our approach combines convex optimization with dynamic programming
techniques applicable for thin graphs. The popular tree-reweighted max-product
(TRMP) method may be seen as solving a particular class of such relaxations,
where the intractable graph is relaxed to a set of spanning trees. We also
consider relaxations to a set of small induced subgraphs, thin subgraphs (e.g.
loops), and a connected tree obtained by ``unwinding'' cycles. In addition, we
propose a new class of multiscale relaxations that introduce ``summary''
variables. The potential benefits of such generalizations include: reducing or
eliminating the ``duality gap'' in hard problems, reducing the number or
Lagrange multipliers in the dual problem, and accelerating convergence of the
iterative optimization procedure.
|
0710.0043
|
Graph rigidity, Cyclic Belief Propagation and Point Pattern Matching
|
cs.CV
|
A recent paper \cite{CaeCaeSchBar06} proposed a provably optimal, polynomial
time method for performing near-isometric point pattern matching by means of
exact probabilistic inference in a chordal graphical model. Their fundamental
result is that the chordal graph in question is shown to be globally rigid,
implying that exact inference provides the same matching solution as exact
inference in a complete graphical model. This implies that the algorithm is
optimal when there is no noise in the point patterns. In this paper, we present
a new graph which is also globally rigid but has an advantage over the graph
proposed in \cite{CaeCaeSchBar06}: its maximal clique size is smaller,
rendering inference significantly more efficient. However, our graph is not
chordal and thus standard Junction Tree algorithms cannot be directly applied.
Nevertheless, we show that loopy belief propagation in such a graph converges
to the optimal solution. This allows us to retain the optimality guarantee in
the noiseless case, while substantially reducing both memory requirements and
processing time. Our experimental results show that the accuracy of the
proposed solution is indistinguishable from that of \cite{CaeCaeSchBar06} when
there is noise in the point patterns.
|
0710.0105
|
Zipf's Law and Avoidance of Excessive Synonymy
|
cs.CL physics.soc-ph
|
Zipf's law states that if words of language are ranked in the order of
decreasing frequency in texts, the frequency of a word is inversely
proportional to its rank. It is very robust as an experimental observation, but
to date it escaped satisfactory theoretical explanation. We suggest that Zipf's
law may arise from the evolution of word semantics dominated by expansion of
meanings and competition of synonyms.
|
0710.0116
|
Distributed MIMO receiver - Achievable rates and upper bounds
|
cs.IT math.IT
|
In this paper we investigate the achievable rate of a system that includes a
nomadic transmitter with several antennas, which is received by multiple
agents, exhibiting independent channel gains and additive circular-symmetric
complex Gaussian noise. In the nomadic regime, we assume that the agents do not
have any decoding ability. These agents process their channel observations and
forward them to the final destination through lossless links with a fixed
capacity. We propose new achievable rates based on elementary compression and
also on a Wyner-Ziv (CEO-like) processing, for both fast fading and block
fading channels, as well as for general discrete channels. The simpler two
agents scheme is solved, up to an implicit equation with a single variable.
Limiting the nomadic transmitter to a circular-symmetric complex Gaussian
signalling, new upper bounds are derived for both fast and block fading, based
on the vector version of the entropy power inequality. These bounds are then
compared to the achievable rates in several extreme scenarios. The asymptotic
setting with numbers of agents and transmitter's antennas taken to infinity is
analyzed. In addition, the upper bounds are analytically shown to be tight in
several examples, while numerical calculations reveal a rather small gap in a
finite $2\times2$ setting. The advantage of the Wyner-Ziv approach over
elementary compression is shown where only the former can achieve the full
diversity-multiplexing tradeoff. We also consider the non-nomadic setting, with
agents that can decode. Here we give an achievable rate, over fast fading
channel, which combines broadcast with dirty paper coding and the decentralized
reception, which was introduced for the nomadic setting.
|
0710.0142
|
LDPC codes in the McEliece cryptosystem: attacks and countermeasures
|
cs.IT math.IT
|
The McEliece cryptosystem is a public-key cryptosystem based on coding theory
that has successfully resisted cryptanalysis for thirty years. The original
version, based on Goppa codes, is able to guarantee a high level of security,
and is faster than competing solutions, like RSA. Despite this, it has been
rarely considered in practical applications, due to two major drawbacks: i)
large size of the public key and ii) low transmission rate. Low-Density
Parity-Check (LDPC) codes are state-of-art forward error correcting codes that
permit to approach the Shannon limit while ensuring limited complexity.
Quasi-Cyclic (QC) LDPC codes are a particular class of LDPC codes, able to join
low complexity encoding of QC codes with high-performing and low-complexity
decoding of LDPC codes. In a previous work it has been proposed to adopt a
particular family of QC-LDPC codes in the McEliece cryptosystem to reduce the
key size and increase the transmission rate. Recently, however, new attacks
have been found that are able to exploit a flaw in the transformation from the
private key to the public one. Such attacks can be effectively countered by
changing the form of some constituent matrices, without altering the system
parameters. This work gives an overview of the QC-LDPC codes-based McEliece
cryptosystem and its cryptanalysis. Two recent versions are considered, and
their ability to counter all the currently known attacks is discussed. A third
version able to reach a higher security level is also proposed. Finally, it is
shown that the new QC-LDPC codes-based cryptosystem scales favorably with the
key length.
|
0710.0169
|
Evaluation experiments on related terms search in Wikipedia: Information
Content and Adapted HITS (In Russian)
|
cs.IR cs.CL
|
The classification of metrics and algorithms search for related terms via
WordNet, Roget's Thesaurus, and Wikipedia was extended to include adapted HITS
algorithm. Evaluation experiments on Information Content and adapted HITS
algorithm are described. The test collection of Russian word pairs with
human-assigned similarity judgments is proposed.
-----
Klassifikacija metrik i algoritmov poiska semanticheski blizkih slov v
tezaurusah WordNet, Rozhe i jenciklopedii Vikipedija rasshirena adaptirovannym
HITS algoritmom. S pomow'ju jeksperimentov v Vikipedii oceneny metrika
Information Content i adaptirovannyj algoritm HITS. Predlozhen resurs dlja
ocenki semanticheskoj blizosti russkih slov.
|
0710.0192
|
Binary quantization using Belief Propagation with decimation over factor
graphs of LDGM codes
|
cs.IT math.IT
|
We propose a new algorithm for binary quantization based on the Belief
Propagation algorithm with decimation over factor graphs of Low Density
Generator Matrix (LDGM) codes. This algorithm, which we call Bias Propagation
(BiP), can be considered as a special case of the Survey Propagation algorithm
proposed for binary quantization by Wainwright et al. [8]. It achieves the same
near-optimal rate-distortion performance with a substantially simpler framework
and 10-100 times faster implementation. We thus challenge the widespread belief
that binary quantization based on sparse linear codes cannot be solved by
simple Belief Propagation algorithms. Finally, we give examples of suitably
irregular LDGM codes that work with the BiP algorithm and show their
performance.
|
0710.0198
|
Z4-Linear Perfect Codes
|
cs.IT math.IT
|
For every $n = 2^k > 8$ there exist exactly $[(k+1)/2]$ mutually
nonequivalent $Z_4$-linear extended perfect codes with distance 4. All these
codes have different ranks.
|
0710.0199
|
Z4-linear Hadamard and extended perfect codes
|
cs.IT math.IT
|
If $N=2^k > 8$ then there exist exactly $[(k-1)/2]$ pairwise nonequivalent
$Z_4$-linear Hadamard $(N,2N,N/2)$-codes and $[(k+1)/2]$ pairwise nonequivalent
$Z_4$-linear extended perfect $(N,2^N/2N,4)$-codes. A recurrent construction of
$Z_4$-linear Hadamard codes is given.
|
0710.0213
|
Optimising the topology of complex neural networks
|
cs.NE cs.AI
|
In this paper, we study instances of complex neural networks, i.e. neural
netwo rks with complex topologies. We use Self-Organizing Map neural networks
whose n eighbourhood relationships are defined by a complex network, to
classify handwr itten digits. We show that topology has a small impact on
performance and robus tness to neuron failures, at least at long learning
times. Performance may howe ver be increased (by almost 10%) by artificial
evolution of the network topo logy. In our experimental conditions, the evolved
networks are more random than their parents, but display a more heterogeneous
degree distribution.
|
0710.0225
|
On the role of autocorrelations in texts
|
cs.CL
|
The task of finding a criterion allowing to distinguish a text from an
arbitrary set of words is rather relevant in itself, for instance, in the
aspect of development of means for internet-content indexing or separating
signals and noise in communication channels. The Zipf law is currently
considered to be the most reliable criterion of this kind [3]. At any rate,
conventional stochastic word sets do not meet this law. The present paper deals
with one of possible criteria based on the determination of the degree of data
compression.
|
0710.0228
|
On the fractal nature of mutual relevance sequences in the Internet news
message flows
|
cs.CL
|
In the task of information retrieval the term relevance is taken to mean
formal conformity of a document given by the retrieval system to user's
information query. As a rule, the documents found by the retrieval system
should be submitted to the user in a certain order. Therefore, a retrieval
perceived as a selection of documents formally solving the user's query, should
be supplemented with a certain procedure of processing a relevant set. It would
be natural to introduce a quantitative measure of document conformity to query,
i.e. the relevance measure. Since no single rule exists for the determination
of the relevance measure, we shall consider two of them which are the simplest
in our opinion. The proposed approach does not suppose any restrictions and can
be applied to other relevance measures.
|
0710.0243
|
High-Order Nonparametric Belief-Propagation for Fast Image Inpainting
|
cs.CV
|
In this paper, we use belief-propagation techniques to develop fast
algorithms for image inpainting. Unlike traditional gradient-based approaches,
which may require many iterations to converge, our techniques achieve
competitive results after only a few iterations. On the other hand, while
belief-propagation techniques are often unable to deal with high-order models
due to the explosion in the size of messages, we avoid this problem by
approximating our high-order prior model using a Gaussian mixture. By using
such an approximation, we are able to inpaint images quickly while at the same
time retaining good visual results.
|
0710.0244
|
Theoretical Engineering and Satellite Comlink of a PTVD-SHAM System
|
cs.CE cs.AR
|
This paper focuses on super helical memory system's design, 'Engineering,
Architectural and Satellite Communications' as a theoretical approach of an
invention-model to 'store time-data'. The current release entails three
concepts: 1- an in-depth theoretical physics engineering of the chip including
its, 2- architectural concept based on VLSI methods, and 3- the time-data
versus data-time algorithm. The 'Parallel Time Varying & Data Super-helical
Access Memory' (PTVD-SHAM), possesses a waterfall effect in its architecture
dealing with the process of voltage output-switch into diverse logic and
quantum states described as 'Boolean logic & image-logic', respectively.
Quantum dot computational methods are explained by utilizing coiled carbon
nanotubes (CCNTs) and CNT field effect transistors (CNFETs) in the chip's
architecture. Quantum confinement, categorized quantum well substrate, and
B-field flux involvements are discussed in theory. Multi-access of coherent
sequences of 'qubit addressing' in any magnitude, gained as pre-defined, here
e.g., the 'big O notation' asymptotically confined into singularity while
possessing a magnitude of 'infinity' for the orientation of array displacement.
Gaussian curvature of k<0 versus k'>(k<0) is debated in aim of specifying the
2D electron gas characteristics, data storage system for defining short and
long time cycles for different CCNT diameters where space-time continuum is
folded by chance for the particle. Precise pre/post data timing for, e.g.,
seismic waves before earthquake mantle-reach event occurrence, including time
varying self-clocking devices in diverse geographic locations for radar systems
is illustrated in the Subsections of the paper. The theoretical fabrication
process, electromigration between chip's components is discussed as well.
|
0710.0262
|
Incomplete Lineage Sorting: Consistent Phylogeny Estimation From
Multiple Loci
|
q-bio.PE cs.CE cs.DS math.PR math.ST stat.TH
|
We introduce a simple algorithm for reconstructing phylogenies from multiple
gene trees in the presence of incomplete lineage sorting, that is, when the
topology of the gene trees may differ from that of the species tree. We show
that our technique is statistically consistent under standard stochastic
assumptions, that is, it returns the correct tree given sufficiently many
unlinked loci. We also show that it can tolerate moderate estimation errors.
|
0710.0291
|
On Outage Behavior of Wideband Slow-Fading Channels
|
cs.IT math.IT
|
This paper investigates point-to-point information transmission over a
wideband slow-fading channel, modeled as an (asymptotically) large number of
independent identically distributed parallel channels, with the random channel
fading realizations remaining constant over the entire coding block. On the one
hand, in the wideband limit the minimum achievable energy per nat required for
reliable transmission, as a random variable, converges in probability to
certain deterministic quantity. On the other hand, the exponential decay rate
of the outage probability, termed as the wideband outage exponent,
characterizes how the number of parallel channels, {\it i.e.}, the
``bandwidth'', should asymptotically scale in order to achieve a targeted
outage probability at a targeted energy per nat. We examine two scenarios: when
the transmitter has no channel state information and adopts uniform transmit
power allocation among parallel channels; and when the transmitter is endowed
with an one-bit channel state feedback for each parallel channel and
accordingly allocates its transmit power. For both scenarios, we evaluate the
wideband minimum energy per nat and the wideband outage exponent, and discuss
their implication for system performance.
|
0710.0410
|
The Theory of Unified Relativity for a Biovielectroluminescence
Phenomenon via Fly's Visual and Imaging System
|
cs.CE cs.CV
|
The elucidation upon fly's neuronal patterns as a link to computer graphics
and memory cards I/O's, is investigated for the phenomenon by propounding a
unified theory of Einstein's two known relativities. It is conclusive that
flies could contribute a certain amount of neuromatrices indicating an imagery
function of a visual-computational system into computer graphics and storage
systems. The visual system involves the time aspect, whereas flies possess
faster pulses compared to humans' visual ability due to the E-field state on an
active fly's eye surface. This behaviour can be tested on a dissected fly
specimen at its ommatidia. Electro-optical contacts and electrodes are wired
through the flesh forming organic emitter layer to stimulate light emission,
thereby to a computer circuit. The next step is applying a threshold voltage
with secondary voltages to the circuit denoting an array of essential
electrodes for bit switch. As a result, circuit's dormant pulses versus active
pulses at the specimen's area are recorded. The outcome matrix possesses a
construction of RGB and time radicals expressing the time problem in
consumption, allocating time into computational algorithms, enhancing the
technology far beyond. The obtained formulation generates consumed distance
cons(x), denoting circuital travel between data source/sink for pixel data and
bendable wavelengths. Once 'image logic' is in place, incorporating this point
of graphical acceleration permits one to enhance graphics and optimize
immensely central processing, data transmissions between memory and computer
visual system. The phenomenon can be mainly used in 360-deg. display/viewing,
3D scanning techniques, military and medicine, a robust and cheap substitution
for e.g. pre-motion pattern analysis, real-time rendering and LCDs.
|
0710.0431
|
New Counting Codes for Distributed Video Coding
|
cs.IT math.IT
|
This paper introduces a new counting code. Its design was motivated by
distributed video coding where, for decoding, error correction methods are
applied to improve predictions. Those error corrections sometimes fail which
results in decoded values worse than the initial prediction. Our code exploits
the fact that bit errors are relatively unlikely events: more than a few bit
errors in a decoded pixel value are rare. With a carefully designed counting
code combined with a prediction those bit errors can be corrected and sometimes
the original pixel value recovered. The error correction improves
significantly. Our new code not only maximizes the Hamming distance between
adjacent (or "near 1") codewords but also between nearby (for example "near 2")
codewords. This is why our code is significantly different from the well-known
maximal counting sequences which have maximal average Hamming distance.
Fortunately, the new counting code can be derived from Gray Codes for every
code word length (i.e. bit depth).
|
0710.0485
|
Prediction with expert advice for the Brier game
|
cs.LG
|
We show that the Brier game of prediction is mixable and find the optimal
learning rate and substitution function for it. The resulting prediction
algorithm is applied to predict results of football and tennis matches. The
theoretical performance guarantee turns out to be rather tight on these data
sets, especially in the case of the more extensive tennis data.
|
0710.0531
|
The Problem of Localization in Networks of Randomly Deployed Nodes:
Asymptotic and Finite Analysis, and Thresholds
|
cs.DM cs.IT cs.NI math.IT
|
We derive the probability that a randomly chosen NL-node over $S$ gets
localized as a function of a variety of parameters. Then, we derive the
probability that the whole network of NL-nodes over $S$ gets localized. In
connection with the asymptotic thresholds, we show the presence of asymptotic
thresholds on the network localization probability in two different scenarios.
The first refers to dense networks, which arise when the domain $S$ is bounded
and the densities of the two kinds of nodes tend to grow unboundedly. The
second kind of thresholds manifest themselves when the considered domain
increases but the number of nodes grow in such a way that the L-node density
remains constant throughout the investigated domain. In this scenario, what
matters is the minimum value of the maximum transmission range averaged over
the fading process, denoted as $d_{max}$, above which the network of NL-nodes
almost surely gets asymptotically localized.
|
0710.0556
|
A Game Theoretic Approach to Quantum Information
|
quant-ph cs.GT cs.IT math.IT
|
This work is an application of game theory to quantum information. In a state
estimate, we are given observations distributed according to an unknown
distribution $P_{\theta}$ (associated with award $Q$), which Nature chooses at
random from the set $\{P_{\theta}: \theta \in \Theta \}$ according to a known
prior distribution $\mu$ on $\Theta$, we produce an estimate $M$ for the
unknown distribution $P_{\theta}$, and in the end, we will suffer a relative
entropy cost $\mathcal{R}(P;M)$, measuring the quality of this estimate,
therefore the whole utility is taken as $P \cdot Q -\mathcal{R}(P; M)$.
In an introduction to strategic game, a sufficient condition for minimax
theorem is obtained; An estimate is explored in the frame of game theory, and
in the view of convex conjugate, we reach one new approach to quantum relative
entropy, correspondingly quantum mutual entropy, and quantum channel capacity,
which are more general, in the sense, without Radon-Nikodym (RN) derivatives.
Also the monotonicity of quantum relative entropy and the additivity of quantum
channel capacity are investigated.
|
0710.0564
|
TP Decoding
|
cs.IT math.IT
|
`Tree pruning' (TP) is an algorithm for probabilistic inference on binary
Markov random fields. It has been recently derived by Dror Weitz and used to
construct the first fully polynomial approximation scheme for counting
independent sets up to the `tree uniqueness threshold.' It can be regarded as a
clever method for pruning the belief propagation computation tree, in such a
way to exactly account for the effect of loops.
In this paper we generalize the original algorithm to make it suitable for
decoding linear codes, and discuss various schemes for pruning the computation
tree. Further, we present the outcomes of numerical simulations on several
linear codes, showing that tree pruning allows to interpolate continuously
between belief propagation and maximum a posteriori decoding. Finally, we
discuss theoretical implications of the new method.
|
0710.0658
|
Detailed Network Measurements Using Sparse Graph Counters: The Theory
|
cs.NI cs.IT math.IT
|
Measuring network flow sizes is important for tasks like accounting/billing,
network forensics and security. Per-flow accounting is considered hard because
it requires that many counters be updated at a very high speed; however, the
large fast memories needed for storing the counters are prohibitively
expensive. Therefore, current approaches aim to obtain approximate flow counts;
that is, to detect large elephant flows and then measure their sizes.
Recently the authors and their collaborators have developed [1] a novel
method for per-flow traffic measurement that is fast, highly memory efficient
and accurate. At the core of this method is a novel counter architecture called
"counter braids.'' In this paper, we analyze the performance of the counter
braid architecture under a Maximum Likelihood (ML) flow size estimation
algorithm and show that it is optimal; that is, the number of bits needed to
store the size of a flow matches the entropy lower bound. While the ML
algorithm is optimal, it is too complex to implement. In [1] we have developed
an easy-to-implement and efficient message passing algorithm for estimating
flow sizes.
|
0710.0672
|
Optimization of supply diversity for the self-assembly of simple objects
in two and three dimensions
|
cs.NE
|
The field of algorithmic self-assembly is concerned with the design and
analysis of self-assembly systems from a computational perspective, that is,
from the perspective of mathematical problems whose study may give insight into
the natural processes through which elementary objects self-assemble into more
complex ones. One of the main problems of algorithmic self-assembly is the
minimum tile set problem (MTSP), which asks for a collection of types of
elementary objects (called tiles) to be found for the self-assembly of an
object having a pre-established shape. Such a collection is to be as concise as
possible, thus minimizing supply diversity, while satisfying a set of stringent
constraints having to do with the termination and other properties of the
self-assembly process from its tile types. We present a study of what we think
is the first practical approach to MTSP. Our study starts with the introduction
of an evolutionary heuristic to tackle MTSP and includes results from extensive
experimentation with the heuristic on the self-assembly of simple objects in
two and three dimensions. The heuristic we introduce combines classic elements
from the field of evolutionary computation with a problem-specific variant of
Pareto dominance into a multi-objective approach to MTSP.
|
0710.0736
|
Colour image segmentation by the vector-valued Allen-Cahn phase-field
model: a multigrid solution
|
cs.CV cs.NA
|
We propose a new method for the numerical solution of a PDE-driven model for
colour image segmentation and give numerical examples of the results. The
method combines the vector-valued Allen-Cahn phase field equation with initial
data fitting terms. This method is known to be closely related to the
Mumford-Shah problem and the level set segmentation by Chan and Vese. Our
numerical solution is performed using a multigrid splitting of a finite element
space, thereby producing an efficient and robust method for the segmentation of
large images.
|
0710.0865
|
Secrecy Capacity of the Wiretap Channel with Noisy Feedback
|
cs.IT cs.CR math.IT
|
In this work, the role of noisy feedback in enhancing the secrecy capacity of
the wiretap channel is investigated. A model is considered in which the
feed-forward and feedback signals share the same noisy channel. More
specifically, a discrete memoryless modulo-additive channel with a full-duplex
destination node is considered first, and it is shown that a 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. Then a half-duplex system is considered, for which 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.
|
0710.0900
|
A New Achievability Scheme for the Relay Channel
|
cs.IT math.IT
|
In this paper, we propose a new coding scheme for the general relay channel.
This coding scheme is in the form of a block Markov code. The transmitter uses
a superposition Markov code. The relay compresses the received signal and maps
the compressed version of the received signal into a codeword conditioned on
the codeword of the previous block. The receiver performs joint decoding after
it has received all of the B blocks. We show that this coding scheme can be
viewed as a generalization of the well-known Compress-And-Forward (CAF) scheme
proposed by Cover and El Gamal. Our coding scheme provides options for
preserving the correlation between the channel inputs of the transmitter and
the relay, which is not possible in the CAF scheme. Thus, our proposed scheme
may potentially yield a larger achievable rate than the CAF scheme.
|
0710.0903
|
Control and Monitoring System for Modular Wireless Robot
|
cs.RO
|
We introduce our concept on the modular wireless robot consisting of three
main modules : main unit, data acquisition and data processing modules. We have
developed a generic prototype with an integrated control and monitoring system
to enhance its flexibility, and to enable simple operation through a web-based
interface accessible wirelessly. In present paper, we focus on the
microcontroller based hardware to enable data acquisition and remote mechanical
control.
|
0710.0937
|
Multichannel algorithm based on generalized positional numeration system
|
cs.IT math.IT
|
This report is devoted to introduction in multichannel algorithm based on
generalized numeration notations (GPN). The internal, external and mixed
account are entered. The concept of the GPN and its classification as
decomposition of an integer on composed of integers is discussed. Realization
of multichannel algorithm on the basis of GPN is introduced. In particular,
some properties of Fibonacci multichannel algorithm are discussed.
|
0710.1001
|
Connectivity of Random 1-Dimensional Networks
|
cs.IT cs.DS math.IT stat.AP
|
An important problem in wireless sensor networks is to find the minimal
number of randomly deployed sensors making a network connected with a given
probability. In practice sensors are often deployed one by one along a
trajectory of a vehicle, so it is natural to assume that arbitrary probability
density functions of distances between successive sensors in a segment are
given. The paper computes the probability of connectivity and coverage of
1-dimensional networks and gives estimates for a minimal number of sensors for
important distributions.
|
0710.1149
|
Z2Z4-linear codes: generator matrices and duality
|
cs.IT cs.DM math.CO math.IT
|
A code ${\cal C}$ is $\Z_2\Z_4$-additive if the set of coordinates can be
partitioned into two subsets $X$ and $Y$ such that the punctured code of ${\cal
C}$ by deleting the coordinates outside $X$ (respectively, $Y$) is a binary
linear code (respectively, a quaternary linear code). In this paper
$\Z_2\Z_4$-additive codes are studied. Their corresponding binary images, via
the Gray map, are $\Z_2\Z_4$-linear codes, which seem to be a very
distinguished class of binary group codes.
As for binary and quaternary linear codes, for these codes the fundamental
parameters are found and standard forms for generator and parity check matrices
are given. For this, the appropriate inner product is deduced and the concept
of duality for $\Z_2\Z_4$-additive codes is defined. Moreover, the parameters
of the dual codes are computed. Finally, some conditions for self-duality of
$\Z_2\Z_4$-additive codes are given.
|
0710.1182
|
Low-Density Parity-Check Codes for Nonergodic Block-Fading Channels
|
cs.IT math.IT
|
We solve the problem of designing powerful low-density parity-check (LDPC)
codes with iterative decoding for the block-fading channel. We first study the
case of maximum-likelihood decoding, and show that the design criterion is
rather straightforward. Unfortunately, optimal constructions for
maximum-likelihood decoding do not perform well under iterative decoding. To
overcome this limitation, we then introduce a new family of full-diversity LDPC
codes that exhibit near-outage-limit performance under iterative decoding for
all block-lengths. This family competes with multiplexed parallel turbo codes
suitable for nonergodic channels and recently reported in the literature.
|
0710.1190
|
Power Efficient Scheduling under Delay Constraints over Multi-user
Wireless Channels
|
cs.NI cs.MA
|
In this paper, we consider the problem of power efficient uplink scheduling
in a Time Division Multiple Access (TDMA) system over a fading wireless
channel. The objective is to minimize the power expenditure of each user
subject to satisfying individual user delay. We make the practical assumption
that the system statistics are unknown, i.e., the probability distributions of
the user arrivals and channel states are unknown. The problem has the structure
of a Constrained Markov Decision Problem (CMDP). Determining an optimal policy
under for the CMDP faces the problems of state space explosion and unknown
system statistics. To tackle the problem of state space explosion, we suggest
determining the transmission rate of a particular user in each slot based on
its channel condition and buffer occupancy only. The rate allocation algorithm
for a particular user is a learning algorithm that learns about the buffer
occupancy and channel states of that user during system execution and thus
addresses the issue of unknown system statistics. Once the rate of each user is
determined, the proposed algorithm schedules the user with the best rate. Our
simulations within an IEEE 802.16 system demonstrate that the algorithm is
indeed able to satisfy the user specified delay constraints. We compare the
performance of our algorithm with the well known M-LWDF algorithm. Moreover, we
demonstrate that the power expended by the users under our algorithm is quite
low.
|
0710.1203
|
Semantic distillation: a method for clustering objects by their
contextual specificity
|
math.PR cs.DB math.ST q-bio.QM stat.ML stat.TH
|
Techniques for data-mining, latent semantic analysis, contextual search of
databases, etc. have long ago been developed by computer scientists working on
information retrieval (IR). Experimental scientists, from all disciplines,
having to analyse large collections of raw experimental data (astronomical,
physical, biological, etc.) have developed powerful methods for their
statistical analysis and for clustering, categorising, and classifying objects.
Finally, physicists have developed a theory of quantum measurement, unifying
the logical, algebraic, and probabilistic aspects of queries into a single
formalism. The purpose of this paper is twofold: first to show that when
formulated at an abstract level, problems from IR, from statistical data
analysis, and from physical measurement theories are very similar and hence can
profitably be cross-fertilised, and, secondly, to propose a novel method of
fuzzy hierarchical clustering, termed \textit{semantic distillation} --
strongly inspired from the theory of quantum measurement --, we developed to
analyse raw data coming from various types of experiments on DNA arrays. We
illustrate the method by analysing DNA arrays experiments and clustering the
genes of the array according to their specificity.
|
0710.1254
|
A Group Theoretic Model for Information
|
cs.IT math.IT
|
In this paper we formalize the notions of information elements and
information lattices, first proposed by Shannon. Exploiting this formalization,
we identify a comprehensive parallelism between information lattices and
subgroup lattices. Qualitatively, we demonstrate isomorphisms between
information lattices and subgroup lattices. Quantitatively, we establish a
decisive approximation relation between the entropy structures of information
lattices and the log-index structures of the corresponding subgroup lattices.
This approximation extends the approximation for joint entropies carried out
previously by Chan and Yeung. As a consequence of our approximation result, we
show that any continuous law holds in general for the entropies of information
elements if and only if the same law holds in general for the log-indices of
subgroups. As an application, by constructing subgroup counterexamples we find
surprisingly that common information, unlike joint information, obeys neither
the submodularity nor the supermodularity law. We emphasize that the notion of
information elements is conceptually significant--formalizing it helps to
reveal the deep connection between information theory and group theory. The
parallelism established in this paper admits an appealing group-action
explanation and provides useful insights into the intrinsic structure among
information elements from a group-theoretic perspective.
|
0710.1275
|
On Convergence Properties of Shannon Entropy
|
cs.IT math.IT
|
Convergence properties of Shannon Entropy are studied. In the differential
setting, it is shown that weak convergence of probability measures, or
convergence in distribution, is not enough for convergence of the associated
differential entropies. A general result for the desired differential entropy
convergence is provided, taking into account both compactly and uncompactly
supported densities. Convergence of differential entropy is also characterized
in terms of the Kullback-Liebler discriminant for densities with fairly general
supports, and it is shown that convergence in variation of probability measures
guarantees such convergence under an appropriate boundedness condition on the
densities involved. Results for the discrete setting are also provided,
allowing for infinitely supported probability measures, by taking advantage of
the equivalence between weak convergence and convergence in variation in this
setting.
|
0710.1280
|
On the Relationship between Mutual Information and Minimum Mean-Square
Errors in Stochastic Dynamical Systems
|
cs.IT math.IT
|
We consider a general stochastic input-output dynamical system with output
evolving in time as the solution to a functional coefficients, It\^{o}'s
stochastic differential equation, excited by an input process. This general
class of stochastic systems encompasses not only the classical communication
channel models, but also a wide variety of engineering systems appearing
through a whole range of applications. For this general setting we find
analogous of known relationships linking input-output mutual information and
minimum mean causal and non-causal square errors, previously established in the
context of additive Gaussian noise communication channels. Relationships are
not only established in terms of time-averaged quantities, but also their
time-instantaneous, dynamical counterparts are presented. The problem of
appropriately introducing in this general framework a signal-to-noise ratio
notion expressed through a signal-to-noise ratio parameter is also taken into
account, identifying conditions for a proper and meaningful interpretation.
|
0710.1325
|
The MIMOME Channel
|
cs.IT math.IT
|
The MIMOME channel is a Gaussian wiretap channel in which the sender,
receiver, and eavesdropper all have multiple antennas. We characterize the
secrecy capacity as the saddle-value of a minimax problem. Among other
implications, our result establishes that a Gaussian distribution maximizes the
secrecy capacity characterization of Csisz{\'a}r and K{\"o}rner when applied to
the MIMOME channel. We also determine a necessary and sufficient condition for
the secrecy capacity to be zero. Large antenna array analysis of this condition
reveals several useful insights into the conditions under which secure
communication is possible.
|
0710.1336
|
Multi-User Diversity vs. Accurate Channel Feedback for MIMO Broadcast
Channels
|
cs.IT math.IT
|
A multiple transmit antenna, single receive antenna (per receiver) downlink
channel with limited channel feedback is considered. Given a constraint on the
total system-wide channel feedback, the following question is considered: is it
preferable to get low-rate feedback from a large number of receivers or to
receive high-rate/high-quality feedback from a smaller number of (randomly
selected) receivers? Acquiring feedback from many users allows multi-user
diversity to be exploited, while high-rate feedback allows for very precise
selection of beamforming directions. It is shown that systems in which a
limited number of users feedback high-rate channel information significantly
outperform low-rate/many user systems. While capacity increases only double
logarithmically with the number of users, the marginal benefit of channel
feedback is very significant up to the point where the CSI is essentially
perfect.
|
0710.1383
|
Log-concavity property of the error probability with application to
local bounds for wireless communications
|
cs.IT math.IT
|
A clear understanding the behavior of the error probability (EP) as a
function of signal-to-noise ratio (SNR) and other system parameters is
fundamental for assessing the design of digital wireless communication
systems.We propose an analytical framework based on the log-concavity property
of the EP which we prove for a wide family of multidimensional modulation
formats in the presence of Gaussian disturbances and fading. Based on this
property, we construct a class of local bounds for the EP that improve known
generic bounds in a given region of the SNR and are invertible, as well as
easily tractable for further analysis. This concept is motivated by the fact
that communication systems often operate with performance in a certain region
of interest (ROI) and, thus, it may be advantageous to have tighter bounds
within this region instead of generic bounds valid for all SNRs. We present a
possible application of these local bounds, but their relevance is beyond the
example made in this paper.
|
0710.1385
|
Cognitive Medium Access: Exploration, Exploitation and Competition
|
cs.IT cs.NI math.IT
|
This paper establishes the equivalence between cognitive medium access and
the competitive multi-armed bandit problem. First, the scenario in which a
single cognitive user wishes to opportunistically exploit the availability of
empty frequency bands in the spectrum with multiple bands is considered. In
this scenario, the availability probability of each channel is unknown to the
cognitive user a priori. Hence efficient medium access strategies must strike a
balance between exploring the availability of other free channels and
exploiting the opportunities identified thus far. By adopting a Bayesian
approach for this classical bandit problem, the optimal medium access strategy
is derived and its underlying recursive structure is illustrated via examples.
To avoid the prohibitive computational complexity of the optimal strategy, a
low complexity asymptotically optimal strategy is developed. The proposed
strategy does not require any prior statistical knowledge about the traffic
pattern on the different channels. Next, the multi-cognitive user scenario is
considered and low complexity medium access protocols, which strike the optimal
balance between exploration and exploitation in such competitive environments,
are developed. Finally, this formalism is extended to the case in which each
cognitive user is capable of sensing and using multiple channels
simultaneously.
|
0710.1404
|
Performance Comparison of Persistence Frameworks
|
cs.DB cs.IR
|
One of the essential and most complex components in the software development
process is the database. The complexity increases when the "orientation" of the
interacting components differs. A persistence framework moves the program data
in its most natural form to and from a permanent data store, the database. Thus
a persistence framework manages the database and the mapping between the
database and the objects. This paper compares the performance of two
persistence frameworks ? Hibernate and iBatis?s SQLMaps using a banking
database. The performance of both of these tools in single and multi-user
environments are evaluated.
|
0710.1418
|
Non-Archimedean Ergodic Theory and Pseudorandom Generators
|
math.DS cs.IT math.IT
|
The paper develops techniques in order to construct computer programs,
pseudorandom number generators (PRNG), that produce uniformly distributed
sequences. The paper exploits an approach that treats standard processor
instructions (arithmetic and bitwise logical ones) as continuous functions on
the space of 2-adic integers. Within this approach, a PRNG is considered as a
dynamical system and is studied by means of the non-Archimedean ergodic theory.
|
0710.1462
|
Minimization of entropy functionals
|
math.OC cs.IT math.IT math.PR
|
Entropy functionals (i.e. convex integral functionals) and extensions of
these functionals are minimized on convex sets. This paper is aimed at reducing
as much as possible the assumptions on the constraint set. Dual equalities and
characterizations of the minimizers are obtained with weak constraint
qualifications.
|
0710.1467
|
Weight Distributions of Hamming Codes
|
cs.IT math.IT math.NT
|
We derive a recursive formula determing the weight distribution of the
[n=(q^m-1)/(q-1), n-m, 3] Hamming code H(m,q), when (m, q-1)=1. Here q is a
prime power. The proof is based on Moisio's idea of using Pless power moment
identity together with exponential sum techniques.
|
0710.1469
|
Weight Distributions of Hamming Codes (II)
|
cs.IT math.IT math.NT
|
In a previous paper, we derived a recursive formula determining the weight
distributions of the [n=(q^m-1)/(q-1)] Hamming code H(m,q), when (m,q-1)=1.
Here q is a prime power. We note here that the formula actually holds for any
positive integer m and any prime power q, without the restriction (m, q-1)=1.
|
0710.1481
|
What's in a Name?
|
cs.CL cs.AI
|
This paper describes experiments on identifying the language of a single name
in isolation or in a document written in a different language. A new corpus has
been compiled and made available, matching names against languages. This corpus
is used in a series of experiments measuring the performance of general
language models and names-only language models on the language identification
task. Conclusions are drawn from the comparison between using general language
models and names-only language models and between identifying the language of
isolated names and the language of very short document fragments. Future
research directions are outlined.
|
0710.1511
|
Demographic growth and the distribution of language sizes
|
physics.data-an cs.CL physics.soc-ph
|
It is argued that the present log-normal distribution of language sizes is,
to a large extent, a consequence of demographic dynamics within the population
of speakers of each language. A two-parameter stochastic multiplicative process
is proposed as a model for the population dynamics of individual languages, and
applied over a period spanning the last ten centuries. The model disregards
language birth and death. A straightforward fitting of the two parameters,
which statistically characterize the population growth rate, predicts a
distribution of language sizes in excellent agreement with empirical data.
Numerical simulations, and the study of the size distribution within language
families, validate the assumptions at the basis of the model.
|
0710.1522
|
Distributed spatial multiplexing with 1-bit feedback
|
cs.IT math.IT
|
We analyze a slow-fading interference network with MN non-cooperating
single-antenna sources and M non-cooperating single-antenna destinations. In
particular, we assume that the sources are divided into M mutually exclusive
groups of N sources each, every group is dedicated to transmit a common message
to a unique destination, all transmissions occur concurrently and in the same
frequency band and a dedicated 1-bit broadcast feedback channel from each
destination to its corresponding group of sources exists. We provide a
feedback-based iterative distributed (multi-user) beamforming algorithm, which
"learns" the channels between each group of sources and its assigned
destination. This algorithm is a straightforward generalization, to the
multi-user case, of the feedback-based iterative distributed beamforming
algorithm proposed recently by Mudumbai et al., in IEEE Trans. Inf. Th.
(submitted) for networks with a single group of sources and a single
destination. Putting the algorithm into a Markov chain context, we provide a
simple convergence proof. We then show that, for M finite and N approaching
infinity, spatial multiplexing based on the beamforming weights produced by the
algorithm achieves full spatial multiplexing gain of M and full per-stream
array gain of N, provided the time spent "learning'' the channels scales
linearly in N. The network is furthermore shown to "crystallize''. Finally, we
characterize the corresponding crystallization rate.
|
0710.1525
|
Efficient Optimally Lazy Algorithms for Minimal-Interval Semantics
|
cs.DS cs.IR
|
Minimal-interval semantics associates with each query over a document a set
of intervals, called witnesses, that are incomparable with respect to inclusion
(i.e., they form an antichain): witnesses define the minimal regions of the
document satisfying the query. Minimal-interval semantics makes it easy to
define and compute several sophisticated proximity operators, provides snippets
for user presentation, and can be used to rank documents. In this paper we
provide algorithms for computing conjunction and disjunction that are linear in
the number of intervals and logarithmic in the number of operands; for
additional operators, such as ordered conjunction and Brouwerian difference, we
provide linear algorithms. In all cases, space is linear in the number of
operands. More importantly, we define a formal notion of optimal laziness, and
either prove it, or prove its impossibility, for each algorithm. We cast our
results in a general framework of antichains of intervals on total orders,
making our algorithms directly applicable to other domains.
|
0710.1589
|
Fast Reliability-based Algorithm of Finding Minimum-weight Codewords for
LDPC Codes
|
cs.IT math.IT
|
Despite the NP hardness of acquiring minimum distance $d_m$ for linear codes
theoretically, in this paper we propose one experimental method of finding
minimum-weight codewords, the weight of which is equal to $d_m$ for LDPC codes.
One existing syndrome decoding method, called serial belief propagation (BP)
with ordered statistic decoding (OSD), is adapted to serve our purpose. We hold
the conjecture that among many candidate error patterns in OSD reprocessing,
modulo 2 addition of the lightest error pattern with one of the left error
patterns may generate a light codeword. When the decoding syndrome changes to
all-zero state, the lightest error pattern reduces to all-zero, the lightest
non-zero error pattern is a valid codeword to update lightest codeword list.
Given sufficient codewords sending, the survived lightest codewords are
likely to be the target. Compared with existing techniques, our method
demonstrates its efficiency in the simulation of several interested LDPC codes.
|
0710.1595
|
Analysis of Fixed Outage Transmission Schemes: A Finer Look at the Full
Multiplexing Point
|
cs.IT math.IT
|
This paper studies the performance of transmission schemes that have rate
that increases with average SNR while maintaining a fixed outage probability.
This is in contrast to the classical Zheng-Tse diversity-multiplexing tradeoff
(DMT) that focuses on increasing rate and decreasing outage probability. Three
different systems are explored: antenna diversity systems, time/frequency
diversity systems, and automatic repeat request (ARQ) systems. In order to
accurately study performance in the fixed outage setting, it is necesary to go
beyond the coarse, asymptotic multiplexing gain metric. In the case of antenna
diversity and time/frequency diversity, an affine approximation to high SNR
outage capacity (i.e., multiplexing gain plus a power/rate offset) accurately
describes performance and shows the very significant benefits of diversity. ARQ
is also seen to provide a significant performance advantage, but even an affine
approximation to outage capacity is unable to capture this advantage and outage
capacity must be directly studied in the non-asymptotic regime.
|
0710.1624
|
Hamiltonian Formulation of Quantum Error Correction and Correlated
Noise: The Effects Of Syndrome Extraction in the Long Time Limit
|
quant-ph cond-mat.stat-mech cs.IT math.IT
|
We analyze the long time behavior of a quantum computer running a quantum
error correction (QEC) code in the presence of a correlated environment.
Starting from a Hamiltonian formulation of realistic noise models, and assuming
that QEC is indeed possible, we find formal expressions for the probability of
a faulty path and the residual decoherence encoded in the reduced density
matrix. Systems with non-zero gate times (``long gates'') are included in our
analysis by using an upper bound on the noise. In order to introduce the local
error probability for a qubit, we assume that propagation of signals through
the environment is slower than the QEC period (hypercube assumption). This
allows an explicit calculation in the case of a generalized spin-boson model
and a quantum frustration model. The key result is a dimensional criterion: If
the correlations decay sufficiently fast, the system evolves toward a
stochastic error model for which the threshold theorem of fault-tolerant
quantum computation has been proven. On the other hand, if the correlations
decay slowly, the traditional proof of this threshold theorem does not hold.
This dimensional criterion bears many similarities to criteria that occur in
the theory of quantum phase transitions.
|
0710.1626
|
Throughput Scaling in Random Wireless Networks: A Non-Hierarchical
Multipath Routing Strategy
|
cs.IT math.IT
|
Franceschetti et al. have recently shown that per-node throughput in an
extended, ad hoc wireless network with $\Theta(n)$ randomly distributed nodes
and multihop routing can be increased from the $\Omega({1 \over \sqrt{n} \log
n})$ scaling demonstrated in the seminal paper of Gupta and Kumar to $\Omega({1
\over \sqrt{n}})$. The goal of the present paper is to understand the
dependence of this interesting result on the principal new features it
introduced relative to Gupta-Kumar: (1) a capacity-based formula for link
transmission bit-rates in terms of received signal-to-interference-and-noise
ratio (SINR); (2) hierarchical routing from sources to destinations through a
system of communal highways; and (3) cell-based routes constructed by
percolation. The conclusion of the present paper is that the improved
throughput scaling is principally due to the percolation-based routing, which
enables shorter hops and, consequently, less interference. This is established
by showing that throughput $\Omega({1 \over \sqrt{n}})$ can be attained by a
system that does not employ highways, but instead uses percolation to
establish, for each source-destination pair, a set of $\Theta(\log n)$ routes
within a narrow routing corridor running from source to destination. As a
result, highways are not essential. In addition, it is shown that throughput
$\Omega({1 \over \sqrt{n}})$ can be attained with the original threshold
transmission bit-rate model, provided that node transmission powers are
permitted to grow with $n$. Thus, the benefit of the capacity bit-rate model is
simply to permit the power to remain bounded, even as the network expands.
|
0710.1870
|
Lossless Representation of Graphs using Distributions
|
math.CO cs.CV
|
We consider complete graphs with edge weights and/or node weights taking
values in some set. In the first part of this paper, we show that a large
number of graphs are completely determined, up to isomorphism, by the
distribution of their sub-triangles. In the second part, we propose graph
representations in terms of one-dimensional distributions (e.g., distribution
of the node weights, sum of adjacent weights, etc.). For the case when the
weights of the graph are real-valued vectors, we show that all graphs, except
for a set of measure zero, are uniquely determined, up to isomorphism, from
these distributions. The motivating application for this paper is the problem
of browsing through large sets of graphs.
|
0710.1879
|
Cyclotomic FFTs with Reduced Additive Complexities Based on a Novel
Common Subexpression Elimination Algorithm
|
cs.IT cs.CC math.CO math.IT
|
In this paper, we first propose a novel common subexpression elimination
(CSE) algorithm for matrix-vector multiplications over characteristic-2 fields.
As opposed to previously proposed CSE algorithms, which usually focus on
complexity savings due to recurrences of subexpressions, our CSE algorithm
achieves two types of complexity reductions, differential savings and
recurrence savings, by taking advantage of the cancelation property of
characteristic-2 fields. Using our CSE algorithm, we reduce the additive
complexities of cyclotomic fast Fourier transforms (CFFTs). Using a weighted
sum of the numbers of multiplications and additions as a metric, our CFFTs
achieve smaller total complexities than previously proposed CFFTs and other
FFTs, requiring both fewer multiplications and fewer additions in many cases.
|
0710.1916
|
Evaluate the Word Error Rate of Binary Block Codes with Square Radius
Probability Density Function
|
cs.IT math.IT
|
The word error rate (WER) of soft-decision-decoded binary block codes rarely
has closed-form. Bounding techniques are widely used to evaluate the
performance of maximum-likelihood decoding algorithm. But the existing bounds
are not tight enough especially for low signal-to-noise ratios and become
looser when a suboptimum decoding algorithm is used. This paper proposes a new
concept named square radius probability density function (SR-PDF) of decision
region to evaluate the WER. Based on the SR-PDF, The WER of binary block codes
can be calculated precisely for ML and suboptimum decoders. Furthermore, for a
long binary block code, SR-PDF can be approximated by Gamma distribution with
only two parameters that can be measured easily. Using this property, two
closed-form approximative expressions are proposed which are very close to the
simulation results of the WER of interesting.
|
0710.1920
|
The Secrecy Capacity of the MIMO Wiretap Channel
|
cs.IT cs.CR math.IT
|
We consider the MIMO wiretap channel, that is a MIMO broadcast channel where
the transmitter sends some confidential information to one user which is a
legitimate receiver, while the other user is an eavesdropper. Perfect secrecy
is achieved when the the transmitter and the legitimate receiver can
communicate at some positive rate, while insuring that the eavesdropper gets
zero bits of information. In this paper, we compute the perfect secrecy
capacity of the multiple antenna MIMO broadcast channel, where the number of
antennas is arbitrary for both the transmitter and the two receivers.
|
0710.1924
|
A Heuristic Routing Mechanism Using a New Addressing Scheme
|
cs.NI cs.AI
|
Current methods of routing are based on network information in the form of
routing tables, in which routing protocols determine how to update the tables
according to the network changes. Despite the variability of data in routing
tables, node addresses are constant. In this paper, we first introduce the new
concept of variable addresses, which results in a novel framework to cope with
routing problems using heuristic solutions. Then we propose a heuristic routing
mechanism based on the application of genes for determination of network
addresses in a variable address network and describe how this method flexibly
solves different problems and induces new ideas in providing integral solutions
for variety of problems. The case of ad-hoc networks is where simulation
results are more supportive and original solutions have been proposed for
issues like mobility.
|
0710.1949
|
Distributed Source Coding Using Continuous-Valued Syndromes
|
cs.IT math.IT
|
This paper addresses the problem of coding a continuous random source
correlated with another source which is only available at the decoder. The
proposed approach is based on the extension of the channel coding concept of
syndrome from the discrete into the continuous domain. If the correlation
between the sources can be described by an additive Gaussian backward channel
and capacity-achieving linear codes are employed, it is shown that the
performance of the system is asymptotically close to the Wyner-Ziv bound. Even
if such an additive channel is not Gaussian, the design procedure can fit the
desired correlation and transmission rate. Experiments based on trellis-coded
quantization show that the proposed system achieves a performance within 3-4 dB
of the theoretical bound in the 0.5-3 bit/sample rate range for any Gaussian
correlation, with a reasonable computational complexity.
|
0710.1962
|
Stanford Matrix Considered Harmful
|
cs.IR
|
This note argues about the validity of web-graph data used in the literature.
|
0710.2018
|
Cognitive Interference Channels with Confidential Messages
|
cs.IT math.IT
|
The cognitive interference channel with confidential messages is studied.
Similarly to the classical two-user interference channel, the cognitive
interference channel consists of two transmitters whose signals interfere at
the two receivers. It is assumed that there is a common message source (message
1) known to both transmitters, and an additional independent message source
(message 2) known only to the cognitive transmitter (transmitter 2). The
cognitive receiver (receiver 2) needs to decode both messages, while the
non-cognitive receiver (receiver 1) should decode only the common message.
Furthermore, message 2 is assumed to be a confidential message which needs to
be kept as secret as possible from receiver 1, which is viewed as an
eavesdropper with regard to message 2. The level of secrecy is measured by the
equivocation rate. A single-letter expression for the capacity-equivocation
region of the discrete memoryless cognitive interference channel is established
and is further explicitly derived for the Gaussian case. Moreover,
particularizing the capacity-equivocation region to the case without a secrecy
constraint, establishes a new capacity theorem for a class of interference
channels, by providing a converse theorem.
|
0710.2037
|
An Affinity Propagation Based method for Vector Quantization Codebook
Design
|
cs.CV
|
In this paper, we firstly modify a parameter in affinity propagation (AP) to
improve its convergence ability, and then, we apply it to vector quantization
(VQ) codebook design problem. In order to improve the quality of the resulted
codebook, we combine the improved AP (IAP) with the conventional LBG algorithm
to generate an effective algorithm call IAP-LBG. According to the experimental
results, the proposed method not only enhances the convergence abilities but
also is capable of providing higher-quality codebooks than conventional LBG
method.
|
0710.2083
|
Association Rules in the Relational Calculus
|
cs.DB cs.LG cs.LO
|
One of the most utilized data mining tasks is the search for association
rules. Association rules represent significant relationships between items in
transactions. We extend the concept of association rule to represent a much
broader class of associations, which we refer to as \emph{entity-relationship
rules.} Semantically, entity-relationship rules express associations between
properties of related objects. Syntactically, these rules are based on a broad
subclass of safe domain relational calculus queries. We propose a new
definition of support and confidence for entity-relationship rules and for the
frequency of entity-relationship queries. We prove that the definition of
frequency satisfies standard probability axioms and the Apriori property.
|
0710.2134
|
Discrete entropies of orthogonal polynomials
|
math.CA cs.IT math-ph math.IT math.MP
|
Let $p_n$ be the $n$-th orthonormal polynomial on the real line, whose zeros
are $\lambda_j^{(n)}$, $j=1, ..., n$. Then for each $j=1, ..., n$, $$ \vec
\Psi_j^2 = (\Psi_{1j}^2, ..., \Psi_{nj}^2) $$ with $$ \Psi_{ij}^2= p_{i-1}^2
(\lambda_j^{(n)}) (\sum_{k=0}^{n-1} p_k^2(\lambda_j^{(n)}))^{-1}, \quad i=1,
>..., n, $$ defines a discrete probability distribution. The Shannon entropy of
the sequence $\{p_n\}$ is consequently defined as $$ \mathcal S_{n,j} =
-\sum_{i=1}^n \Psi_{ij}^{2} \log (\Psi_{ij}^{2}) . $$ In the case of Chebyshev
polynomials of the first and second kinds an explicit and closed formula for
$\mathcal S_{n,j}$ is obtained, revealing interesting connections with the
number theory. Besides, several results of numerical computations exemplifying
the behavior of $\mathcal S_{n,j}$ for other families are also presented.
|
0710.2156
|
Collaborative OLAP with Tag Clouds: Web 2.0 OLAP Formalism and
Experimental Evaluation
|
cs.DB
|
Increasingly, business projects are ephemeral. New Business Intelligence
tools must support ad-lib data sources and quick perusal. Meanwhile, tag clouds
are a popular community-driven visualization technique. Hence, we investigate
tag-cloud views with support for OLAP operations such as roll-ups, slices,
dices, clustering, and drill-downs. As a case study, we implemented an
application where users can upload data and immediately navigate through its ad
hoc dimensions. To support social networking, views can be easily shared and
embedded in other Web sites. Algorithmically, our tag-cloud views are
approximate range top-k queries over spontaneous data cubes. We present
experimental evidence that iceberg cuboids provide adequate online
approximations. We benchmark several browser-oblivious tag-cloud layout
optimizations.
|
0710.2227
|
A System for Predicting Subcellular Localization of Yeast Genome Using
Neural Network
|
cs.NE cs.AI
|
The subcellular location of a protein can provide valuable information about
its function. With the rapid increase of sequenced genomic data, the need for
an automated and accurate tool to predict subcellular localization becomes
increasingly important. Many efforts have been made to predict protein
subcellular localization. This paper aims to merge the artificial neural
networks and bioinformatics to predict the location of protein in yeast genome.
We introduce a new subcellular prediction method based on a backpropagation
neural network. The results show that the prediction within an error limit of 5
to 10 percentage can be achieved with the system.
|
0710.2228
|
Recommendation model based on opinion diffusion
|
physics.soc-ph cs.CY cs.IR physics.data-an
|
Information overload in the modern society calls for highly efficient
recommendation algorithms. In this letter we present a novel diffusion based
recommendation model, with users' ratings built into a transition matrix. To
speed up computation we introduce a Green function method. The numerical tests
on a benchmark database show that our prediction is superior to the standard
recommendation methods.
|
0710.2231
|
Comparison and Combination of State-of-the-art Techniques for
Handwritten Character Recognition: Topping the MNIST Benchmark
|
cs.CV
|
Although the recognition of isolated handwritten digits has been a research
topic for many years, it continues to be of interest for the research community
and for commercial applications. We show that despite the maturity of the
field, different approaches still deliver results that vary enough to allow
improvements by using their combination. We do so by choosing four
well-motivated state-of-the-art recognition systems for which results on the
standard MNIST benchmark are available. When comparing the errors made, we
observe that the errors made differ between all four systems, suggesting the
use of classifier combination. We then determine the error rate of a
hypothetical system that combines the output of the four systems. The result
obtained in this manner is an error rate of 0.35% on the MNIST data, the best
result published so far. We furthermore discuss the statistical significance of
the combined result and of the results of the individual classifiers.
|
0710.2243
|
Edge Local Complementation and Equivalence of Binary Linear Codes
|
math.CO cs.IT math.IT
|
Orbits of graphs under the operation edge local complementation (ELC) are
defined. We show that the ELC orbit of a bipartite graph corresponds to the
equivalence class of a binary linear code. The information sets and the minimum
distance of a code can be derived from the corresponding ELC orbit. By
extending earlier results on local complementation (LC) orbits, we classify the
ELC orbits of all graphs on up to 12 vertices. We also give a new method for
classifying binary linear codes, with running time comparable to the best known
algorithm.
|
0710.2268
|
Complexity of some Path Problems in DAGs and Linear Orders
|
math.CO cs.IT math.IT
|
We investigate here the computational complexity of three natural problems in
directed acyclic graphs. We prove their NP Completeness and consider their
restrictions to linear orders.
|
0710.2446
|
The structure of verbal sequences analyzed with unsupervised learning
techniques
|
cs.CL cs.AI cs.LG
|
Data mining allows the exploration of sequences of phenomena, whereas one
usually tends to focus on isolated phenomena or on the relation between two
phenomena. It offers invaluable tools for theoretical analyses and exploration
of the structure of sentences, texts, dialogues, and speech. We report here the
results of an attempt at using it for inspecting sequences of verbs from French
accounts of road accidents. This analysis comes from an original approach of
unsupervised training allowing the discovery of the structure of sequential
data. The entries of the analyzer were only made of the verbs appearing in the
sentences. It provided a classification of the links between two successive
verbs into four distinct clusters, allowing thus text segmentation. We give
here an interpretation of these clusters by applying a statistical analysis to
independent semantic annotations.
|
0710.2496
|
Regression estimation from an individual stable sequence
|
math.PR cs.IT math.IT math.ST stat.TH
|
We consider univariate regression estimation from an individual (non-random)
sequence $(x_1,y_1),(x_2,y_2), ... \in \real \times \real$, which is stable in
the sense that for each interval $A \subseteq \real$, (i) the limiting relative
frequency of $A$ under $x_1, x_2, ...$ is governed by an unknown probability
distribution $\mu$, and (ii) the limiting average of those $y_i$ with $x_i \in
A$ is governed by an unknown regression function $m(\cdot)$.
A computationally simple scheme for estimating $m(\cdot)$ is exhibited, and
is shown to be $L_2$ consistent for stable sequences $\{(x_i,y_i)\}$ such that
$\{y_i\}$ is bounded and there is a known upper bound for the variation of
$m(\cdot)$ on intervals of the form $(-i,i]$, $i \geq 1$. Complementing this
positive result, it is shown that there is no consistent estimation scheme for
the family of stable sequences whose regression functions have finite
variation, even under the restriction that $x_i \in [0,1]$ and $y_i$ is
binary-valued.
|
0710.2500
|
Density estimation from an individual numerical sequence
|
math.PR cs.IT math.IT math.ST stat.TH
|
This paper considers estimation of a univariate density from an individual
numerical sequence. It is assumed that (i) the limiting relative frequencies of
the numerical sequence are governed by an unknown density, and (ii) there is a
known upper bound for the variation of the density on an increasing sequence of
intervals. A simple estimation scheme is proposed, and is shown to be $L_1$
consistent when (i) and (ii) apply. In addition it is shown that there is no
consistent estimation scheme for the set of individual sequences satisfying
only condition (i).
|
0710.2553
|
Capacity of Linear Two-hop Mesh Networks with Rate Splitting,
Decode-and-forward Relaying and Cooperation
|
cs.IT math.IT
|
A linear mesh network is considered in which a single user per cell
communicates to a local base station via a dedicated relay (two-hop
communication). Exploiting the possibly relevant inter-cell channel gains, rate
splitting with successive cancellation in both hops is investigated as a
promising solution to improve the rate of basic single-rate communications.
Then, an alternative solution is proposed that attempts to improve the
performance of the second hop (from the relays to base stations) by cooperative
transmission among the relay stations. The cooperative scheme leverages the
common information obtained by the relays as a by-product of the use of rate
splitting in the first hop. Numerical results bring insight into the conditions
(network topology and power constraints) under which rate splitting, with
possible relay cooperation, is beneficial. Multi-cell processing (joint
decoding at the base stations) is also considered for reference.
|
0710.2604
|
Efficient Skyline Querying with Variable User Preferences on Nominal
Attributes
|
cs.DB
|
Current skyline evaluation techniques assume a fixed ordering on the
attributes. However, dynamic preferences on nominal attributes are more
realistic in known applications. In order to generate online response for any
such preference issued by a user, we propose two methods of different
characteristics. The first one is a semi-materialization method and the second
is an adaptive SFS method. Finally, we conduct experiments to show the
efficiency of our proposed algorithms.
|
0710.2611
|
Geometric Analogue of Holographic Reduced Representation
|
cs.AI quant-ph
|
Holographic reduced representations (HRR) are based on superpositions of
convolution-bound $n$-tuples, but the $n$-tuples cannot be regarded as vectors
since the formalism is basis dependent. This is why HRR cannot be associated
with geometric structures. Replacing convolutions by geometric products one
arrives at reduced representations analogous to HRR but interpretable in terms
of geometry. Variable bindings occurring in both HRR and its geometric analogue
mathematically correspond to two different representations of
$Z_2\times...\times Z_2$ (the additive group of binary $n$-tuples with addition
modulo 2). As opposed to standard HRR, variable binding performed by means of
geometric product allows for computing exact inverses of all nonzero vectors, a
procedure even simpler than approximate inverses employed in HRR. The formal
structure of the new reduced representation is analogous to cartoon
computation, a geometric analogue of quantum computation.
|
0710.2659
|
Rigidity and persistence for ensuring shape maintenance of multiagent
meta formations (ext'd version)
|
cs.MA cs.DM
|
This paper treats the problem of the merging of formations, where the
underlying model of a formation is graphical. We first analyze the rigidity and
persistence of meta-formations, which are formations obtained by connecting
several rigid or persistent formations. Persistence is a generalization to
directed graphs of the undirected notion of rigidity. In the context of moving
autonomous agent formations, persistence characterizes the efficacy of a
directed structure of unilateral distance constraints seeking to preserve a
formation shape. We derive then, for agents evolving in a two- or
three-dimensional space, the conditions under which a set of persistent
formations can be merged into a persistent meta-formation, and give the minimal
number of interconnections needed for such a merging. We also give conditions
for a meta-formation obtained by merging several persistent formations to be
persistent.
|
0710.2674
|
Linguistic Information Energy
|
cs.CL cs.IT math.IT
|
In this treatment a text is considered to be a series of word impulses which
are read at a constant rate. The brain then assembles these units of
information into higher units of meaning. A classical systems approach is used
to model an initial part of this assembly process. The concepts of linguistic
system response, information energy, and ordering energy are defined and
analyzed. Finally, as a demonstration, information energy is used to estimate
the publication dates of a series of texts and the similarity of a set of
texts.
|
0710.2705
|
Fingerprinting with Minimum Distance Decoding
|
cs.IT cs.CR math.IT
|
This work adopts an information theoretic framework for the design of
collusion-resistant coding/decoding schemes for digital fingerprinting. More
specifically, the minimum distance decision rule is used to identify 1 out of t
pirates. Achievable rates, under this detection rule, are characterized in two
distinct scenarios. First, we consider the averaging attack where a random
coding argument is used to show that the rate 1/2 is achievable with t=2
pirates. Our study is then extended to the general case of arbitrary $t$
highlighting the underlying complexity-performance tradeoff. Overall, these
results establish the significant performance gains offered by minimum distance
decoding as compared to other approaches based on orthogonal codes and
correlation detectors. In the second scenario, we characterize the achievable
rates, with minimum distance decoding, under any collusion attack that
satisfies the marking assumption. For t=2 pirates, we show that the rate
$1-H(0.25)\approx 0.188$ is achievable using an ensemble of random linear
codes. For $t\geq 3$, the existence of a non-resolvable collusion attack, with
minimum distance decoding, for any non-zero rate is established. Inspired by
our theoretical analysis, we then construct coding/decoding schemes for
fingerprinting based on the celebrated Belief-Propagation framework. Using an
explicit repeat-accumulate code, we obtain a vanishingly small probability of
misidentification at rate 1/3 under averaging attack with t=2. For collusion
attacks which satisfy the marking assumption, we use a more sophisticated
accumulate repeat accumulate code to obtain a vanishingly small
misidentification probability at rate 1/9 with t=2. These results represent a
marked improvement over the best available designs in the literature.
|
0710.2782
|
Effective linkage learning using low-order statistics and clustering
|
cs.NE cs.AI
|
The adoption of probabilistic models for the best individuals found so far is
a powerful approach for evolutionary computation. Increasingly more complex
models have been used by estimation of distribution algorithms (EDAs), which
often result better effectiveness on finding the global optima for hard
optimization problems. Supervised and unsupervised learning of Bayesian
networks are very effective options, since those models are able to capture
interactions of high order among the variables of a problem. Diversity
preservation, through niching techniques, has also shown to be very important
to allow the identification of the problem structure as much as for keeping
several global optima. Recently, clustering was evaluated as an effective
niching technique for EDAs, but the performance of simpler low-order EDAs was
not shown to be much improved by clustering, except for some simple multimodal
problems. This work proposes and evaluates a combination operator guided by a
measure from information theory which allows a clustered low-order EDA to
effectively solve a comprehensive range of benchmark optimization problems.
|
0710.2848
|
Consistency of trace norm minimization
|
cs.LG
|
Regularization by the sum of singular values, also referred to as the trace
norm, is a popular technique for estimating low rank rectangular matrices. In
this paper, we extend some of the consistency results of the Lasso to provide
necessary and sufficient conditions for rank consistency of trace norm
minimization with the square loss. We also provide an adaptive version that is
rank consistent even when the necessary condition for the non adaptive version
is not fulfilled.
|
0710.2852
|
Generating models for temporal representations
|
cs.CL
|
We discuss the use of model building for temporal representations. We chose
Polish to illustrate our discussion because it has an interesting aspectual
system, but the points we wish to make are not language specific. Rather, our
goal is to develop theoretical and computational tools for temporal model
building tasks in computational semantics. To this end, we present a
first-order theory of time and events which is rich enough to capture
interesting semantic distinctions, and an algorithm which takes minimal models
for first-order theories and systematically attempts to ``perturb'' their
temporal component to provide non-minimal, but semantically significant,
models.
|
0710.2889
|
An efficient reduction of ranking to classification
|
cs.LG cs.IR
|
This paper describes an efficient reduction of the learning problem of
ranking to binary classification. The reduction guarantees an average pairwise
misranking regret of at most that of the binary classifier regret, improving a
recent result of Balcan et al which only guarantees a factor of 2. Moreover,
our reduction applies to a broader class of ranking loss functions, admits a
simpler proof, and the expected running time complexity of our algorithm in
terms of number of calls to a classifier or preference function is improved
from $\Omega(n^2)$ to $O(n \log n)$. In addition, when the top $k$ ranked
elements only are required ($k \ll n$), as in many applications in information
extraction or search engines, the time complexity of our algorithm can be
further reduced to $O(k \log k + n)$. Our reduction and algorithm are thus
practical for realistic applications where the number of points to rank exceeds
several thousands. Much of our results also extend beyond the bipartite case
previously studied.
Our rediction is a randomized one. To complement our result, we also derive
lower bounds on any deterministic reduction from binary (preference)
classification to ranking, implying that our use of a randomized reduction is
essentially necessary for the guarantees we provide.
|
0710.2988
|
Using Description Logics for Recognising Textual Entailment
|
cs.CL
|
The aim of this paper is to show how we can handle the Recognising Textual
Entailment (RTE) task by using Description Logics (DLs). To do this, we propose
a representation of natural language semantics in DLs inspired by existing
representations in first-order logic. But our most significant contribution is
the definition of two novel inference tasks: A-Box saturation and subgraph
detection which are crucial for our approach to RTE.
|
0710.3027
|
Classical Capacities of Averaged and Compound Quantum Channels
|
quant-ph cs.IT math-ph math.IT math.MP
|
We determine the capacity of compound classical-quantum channels. As a
consequence we obtain the capacity formula for the averaged classical-quantum
channels. The capacity result for compound channels demonstrates, as in the
classical setting, the existence of reliable universal classical-quantum codes
in scenarios where the only a priori information about the channel used for the
transmission of information is that it belongs to a given set of memoryless
classical-quantum channels. Our approach is based on the universal classical
approximation of the quantum relative entropy which in turn relies on the
universal hypothesis testing results.
|
0710.3185
|
Fuzzy Modeling of Electrical Impedance Tomography Image of the Lungs
|
cs.AI cs.CV
|
Electrical Impedance Tomography (EIT) is a functional imaging method that is
being developed for bedside use in critical care medicine. Aiming at improving
the chest anatomical resolution of EIT images we developed a fuzzy model based
on EIT high temporal resolution and the functional information contained in the
pulmonary perfusion and ventilation signals. EIT data from an experimental
animal model were collected during normal ventilation and apnea while an
injection of hypertonic saline was used as a reference . The fuzzy model was
elaborated in three parts: a modeling of the heart, a pulmonary map from
ventilation images and, a pulmonary map from perfusion images. Image
segmentation was performed using a threshold method and a ventilation/perfusion
map was generated. EIT images treated by the fuzzy model were compared with the
hypertonic saline injection method and CT-scan images, presenting good results
in both qualitative (the image obtained by the model was very similar to that
of the CT-scan) and quantitative (the ROC curve provided an area equal to 0.93)
point of view. Undoubtedly, these results represent an important step in the
EIT images area, since they open the possibility of developing EIT-based
bedside clinical methods, which are not available nowadays. These achievements
could serve as the base to develop EIT diagnosis system for some
life-threatening diseases commonly found in critical care medicine.
|
0710.3246
|
Bloom maps
|
cs.DS cs.IT math.IT
|
We consider the problem of succinctly encoding a static map to support
approximate queries. We derive upper and lower bounds on the space requirements
in terms of the error rate and the entropy of the distribution of values over
keys: our bounds differ by a factor log e. For the upper bound we introduce a
novel data structure, the Bloom map, generalising the Bloom filter to this
problem. The lower bound follows from an information theoretic argument.
|
0710.3279
|
Resource Allocation for Delay Differentiated Traffic in Multiuser OFDM
Systems
|
cs.NI cs.IT math.IT
|
Most existing work on adaptive allocation of subcarriers and power in
multiuser orthogonal frequency division multiplexing (OFDM) systems has focused
on homogeneous traffic consisting solely of either delay-constrained data
(guaranteed service) or non-delay-constrained data (best-effort service). In
this paper, we investigate the resource allocation problem in a heterogeneous
multiuser OFDM system with both delay-constrained (DC) and
non-delay-constrained (NDC) traffic. The objective is to maximize the sum-rate
of all the users with NDC traffic while maintaining guaranteed rates for the
users with DC traffic under a total transmit power constraint. Through our
analysis we show that the optimal power allocation over subcarriers follows a
multi-level water-filling principle; moreover, the valid candidates competing
for each subcarrier include only one NDC user but all DC users. By converting
this combinatorial problem with exponential complexity into a convex problem or
showing that it can be solved in the dual domain, efficient iterative
algorithms are proposed to find the optimal solutions. To further reduce the
computational cost, a low-complexity suboptimal algorithm is also developed.
Numerical studies are conducted to evaluate the performance the proposed
algorithms in terms of service outage probability, achievable transmission rate
pairs for DC and NDC traffic, and multiuser diversity.
|
0710.3283
|
Effects of Non-Identical Rayleigh Fading on Differential Unitary
Space-Time Modulation
|
cs.PF cs.IT math.IT
|
This paper has been withdrawn by the author.
|
0710.3285
|
Nontraditional Scoring of C-tests
|
cs.CY cs.CL
|
In C-tests the hypothesis of items local independence is violated, which
doesn't permit to consider them as real tests. It is suggested to determine the
distances between separate C-test items (blanks) and to combine items into
clusters. Weights, inversely proportional to the number of items in
corresponding clusters, are assigned to items. As a result, the C-test
structure becomes similar to the structure of classical tests, without
violation of local independence hypothesis.
|
0710.3375
|
On the Capacity of Interference Channels with One Cooperating
Transmitter
|
cs.IT math.IT
|
Inner and outer bounds are established on the capacity region of two-sender,
two-receiver interference channels where one transmitter knows both messages.
The transmitter with extra knowledge is referred to as being cognitive. The
inner bound is based on strategies that generalize prior work, and include
rate-splitting, Gel'fand-Pinsker coding and cooperative transmission. A general
outer bound is based on the Nair-El Gamal outer bound for broadcast channels. A
simpler bound is presented for the case in which one of the decoders can decode
both messages. The bounds are evaluated and compared for Gaussian channels.
|
0710.3427
|
Error Correction Capability of Column-Weight-Three LDPC Codes
|
cs.IT math.IT
|
In this paper, we investigate the error correction capability of
column-weight-three LDPC codes when decoded using the Gallager A algorithm. We
prove that the necessary condition for a code to correct $k \geq 5$ errors is
to avoid cycles of length up to $2k$ in its Tanner graph. As a consequence of
this result, we show that given any $\alpha>0, \exists N $ such that $\forall
n>N$, no code in the ensemble of column-weight-three codes can correct all
$\alpha n$ or fewer errors. We extend these results to the bit flipping
algorithm.
|
0710.3502
|
Using Synchronic and Diachronic Relations for Summarizing Multiple
Documents Describing Evolving Events
|
cs.CL cs.IR
|
In this paper we present a fresh look at the problem of summarizing evolving
events from multiple sources. After a discussion concerning the nature of
evolving events we introduce a distinction between linearly and non-linearly
evolving events. We present then a general methodology for the automatic
creation of summaries from evolving events. At its heart lie the notions of
Synchronic and Diachronic cross-document Relations (SDRs), whose aim is the
identification of similarities and differences between sources, from a
synchronical and diachronical perspective. SDRs do not connect documents or
textual elements found therein, but structures one might call messages.
Applying this methodology will yield a set of messages and relations, SDRs,
connecting them, that is a graph which we call grid. We will show how such a
grid can be considered as the starting point of a Natural Language Generation
System. The methodology is evaluated in two case-studies, one for linearly
evolving events (descriptions of football matches) and another one for
non-linearly evolving events (terrorist incidents involving hostages). In both
cases we evaluate the results produced by our computational systems.
|
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