id
stringlengths
9
16
title
stringlengths
4
278
categories
stringlengths
5
104
abstract
stringlengths
6
4.09k
0801.0139
Principles of the Concept-Oriented Data Model
cs.DB
In the paper a new approach to data representation and manipulation is described, which is called the concept-oriented data model (CODM). It is supposed that items represent data units, which are stored in concepts. A concept is a combination of superconcepts, which determine the concept's dimensionality or properties. An item is a combination of superitems taken by one from all the superconcepts. An item stores a combination of references to its superitems. The references implement inclusion relation or attribute-value relation among items. A concept-oriented database is defined by its concept structure called syntax or schema and its item structure called semantics. The model defines formal transformations of syntax and semantics including the canonical semantics where all concepts are merged and the data semantics is represented by one set of items. The concept-oriented data model treats relations as subconcepts where items are instances of the relations. Multi-valued attributes are defined via subconcepts as a view on the database semantics rather than as a built-in mechanism. The model includes concept-oriented query language, which is based on collection manipulations. It also has such mechanisms as aggregation and inference based on semantics propagation through the database schema.
0801.0184
The Existence of Strongly-MDS Convolutional Codes
math.OC cs.IT math.IT
It is known that maximum distance separable and maximum distance profile convolutional codes exist over large enough finite fields of any characteristic for all parameters $(n,k,\delta)$. It has been conjectured that the same is true for convolutional codes that are strongly maximum distance separable. Using methods from linear systems theory, we resolve this conjecture by showing that, over a large enough finite field of any characteristic, codes which are simultaneously maximum distance profile and strongly maximum distance separable exist for all parameters $(n,k,\delta)$.
0801.0209
Effective symbolic dynamics, random points, statistical behavior, complexity and entropy
math.DS cs.IT math.IT math.PR
We consider the dynamical behavior of Martin-L\"of random points in dynamical systems over metric spaces with a computable dynamics and a computable invariant measure. We use computable partitions to define a sort of effective symbolic model for the dynamics. Through this construction we prove that such points have typical statistical behavior (the behavior which is typical in the Birkhoff ergodic theorem) and are recurrent. We introduce and compare some notions of complexity for orbits in dynamical systems and prove: (i) that the complexity of the orbits of random points equals the Kolmogorov-Sina\"i entropy of the system, (ii) that the supremum of the complexity of orbits equals the topological entropy.
0801.0232
Does intelligence imply contradiction?
cs.AI cs.LO
Contradiction is often seen as a defect of intelligent systems and a dangerous limitation on efficiency. In this paper we raise the question of whether, on the contrary, it could be considered a key tool in increasing intelligence in biological structures. A possible way of answering this question in a mathematical context is shown, formulating a proposition that suggests a link between intelligence and contradiction. A concrete approach is presented in the well-defined setting of cellular automata. Here we define the models of ``observer'', ``entity'', ``environment'', ``intelligence'' and ``contradiction''. These definitions, which roughly correspond to the common meaning of these words, allow us to deduce a simple but strong result about these concepts in an unbiased, mathematical manner. Evidence for a real-world counterpart to the demonstrated formal link between intelligence and contradiction is provided by three computational experiments.
0801.0249
A mathematical formalism for agent-based modeling
cs.MA cs.DM math.CO
Many complex systems can be modeled as multiagent systems in which the constituent entities (agents) interact with each other. The global dynamics of such a system is determined by the nature of the local interactions among the agents. Since it is difficult to formally analyze complex multiagent systems, they are often studied through computer simulations. While computer simulations can be very useful, results obtained through simulations do not formally validate the observed behavior. Thus, there is a need for a mathematical framework which one can use to represent multiagent systems and formally establish their properties. This work contains a brief exposition of some known mathematical frameworks that can model multiagent systems. The focus is on one such framework, namely that of finite dynamical systems. Both, deterministic and stochastic versions of this framework are discussed. The paper contains a sampling of the mathematical results from the literature to show how finite dynamical systems can be used to carry out a rigorous study of the properties of multiagent systems and it is shown how the framework can also serve as a universal model for computation.
0801.0253
Toward a statistical mechanics of four letter words
q-bio.NC cs.CL physics.data-an physics.soc-ph
We consider words as a network of interacting letters, and approximate the probability distribution of states taken on by this network. Despite the intuition that the rules of English spelling are highly combinatorial (and arbitrary), we find that maximum entropy models consistent with pairwise correlations among letters provide a surprisingly good approximation to the full statistics of four letter words, capturing ~92% of the multi-information among letters and even "discovering" real words that were not represented in the data from which the pairwise correlations were estimated. The maximum entropy model defines an energy landscape on the space of possible words, and local minima in this landscape account for nearly two-thirds of words used in written English.
0801.0275
Estimating Signals with Finite Rate of Innovation from Noisy Samples: A Stochastic Algorithm
stat.AP cs.IT math.IT
As an example of the recently-introduced concept of rate of innovation, signals that are linear combinations of a finite number of Diracs per unit time can be acquired by linear filtering followed by uniform sampling. However, in reality, samples are rarely noiseless. In this paper, we introduce a novel stochastic algorithm to reconstruct a signal with finite rate of innovation from its noisy samples. Even though variants of this problem has been approached previously, satisfactory solutions are only available for certain classes of sampling kernels, for example kernels which satisfy the Strang-Fix condition. In this paper, we consider the infinite-support Gaussian kernel, which does not satisfy the Strang-Fix condition. Other classes of kernels can be employed. Our algorithm is based on Gibbs sampling, a Markov chain Monte Carlo (MCMC) method. Extensive numerical simulations demonstrate the accuracy and robustness of our algorithm.
0801.0340
Sum Rate Maximization using Linear Precoding and Decoding in the Multiuser MIMO Downlink
cs.IT math.IT
We propose an algorithm to maximize the instantaneous sum data rate transmitted by a base station in the downlink of a multiuser multiple-input, multiple-output system. The transmitter and the receivers may each be equipped with multiple antennas and each user may receive more than one data stream. We show that maximizing the sum rate is closely linked to minimizing the product of mean squared errors (PMSE). The algorithm employs an uplink/downlink duality to iteratively design transmit-receive linear precoders, decoders, and power allocations that minimize the PMSE for all data streams under a sum power constraint. Numerical simulations illustrate the effectiveness of the algorithm and support the use of the PMSE criterion in maximizing the overall instantaneous data rate.
0801.0341
Exactness of Belief Propagation for Some Graphical Models with Loops
cond-mat.stat-mech cond-mat.other cs.AI cs.IT math.IT
It is well known that an arbitrary graphical model of statistical inference defined on a tree, i.e. on a graph without loops, is solved exactly and efficiently by an iterative Belief Propagation (BP) algorithm convergent to unique minimum of the so-called Bethe free energy functional. For a general graphical model on a loopy graph the functional may show multiple minima, the iterative BP algorithm may converge to one of the minima or may not converge at all, and the global minimum of the Bethe free energy functional is not guaranteed to correspond to the optimal Maximum-Likelihood (ML) solution in the zero-temperature limit. However, there are exceptions to this general rule, discussed in \cite{05KW} and \cite{08BSS} in two different contexts, where zero-temperature version of the BP algorithm finds ML solution for special models on graphs with loops. These two models share a key feature: their ML solutions can be found by an efficient Linear Programming (LP) algorithm with a Totally-Uni-Modular (TUM) matrix of constraints. Generalizing the two models we consider a class of graphical models reducible in the zero temperature limit to LP with TUM constraints. Assuming that a gedanken algorithm, g-BP, funding the global minimum of the Bethe free energy is available we show that in the limit of zero temperature g-BP outputs the ML solution. Our consideration is based on equivalence established between gapless Linear Programming (LP) relaxation of the graphical model in the $T\to 0$ limit and respective LP version of the Bethe-Free energy minimization.
0801.0352
The price of certainty: "waterslide curves" and the gap to capacity
cs.IT math.IT
The classical problem of reliable point-to-point digital communication is to achieve a low probability of error while keeping the rate high and the total power consumption small. Traditional information-theoretic analysis uses `waterfall' curves to convey the revolutionary idea that unboundedly low probabilities of bit-error are attainable using only finite transmit power. However, practitioners have long observed that the decoder complexity, and hence the total power consumption, goes up when attempting to use sophisticated codes that operate close to the waterfall curve. This paper gives an explicit model for power consumption at an idealized decoder that allows for extreme parallelism in implementation. The decoder architecture is in the spirit of message passing and iterative decoding for sparse-graph codes. Generalized sphere-packing arguments are used to derive lower bounds on the decoding power needed for any possible code given only the gap from the Shannon limit and the desired probability of error. As the gap goes to zero, the energy per bit spent in decoding is shown to go to infinity. This suggests that to optimize total power, the transmitter should operate at a power that is strictly above the minimum demanded by the Shannon capacity. The lower bound is plotted to show an unavoidable tradeoff between the average bit-error probability and the total power used in transmission and decoding. In the spirit of conventional waterfall curves, we call these `waterslide' curves.
0801.0354
Kolmogorov complexity in perspective
math.LO cs.CC cs.IT math.IT
We survey the diverse approaches to the notion of information content: from Shannon entropy to Kolmogorov complexity. The main applications of Kolmogorov complexity are presented namely, the mathematical notion of randomness (which goes back to the 60's with the work of Martin-Lof, Schnorr, Chaitin, Levin), and classification, which is a recent idea with provocative implementation by Vitanyi and Cilibrasi.
0801.0386
Spam: It's Not Just for Inboxes and Search Engines! Making Hirsch h-index Robust to Scientospam
cs.DL cs.IR
What is the 'level of excellence' of a scientist and the real impact of his/her work upon the scientific thinking and practising? How can we design a fair, an unbiased metric -- and most importantly -- a metric robust to manipulation?
0801.0390
Staring at Economic Aggregators through Information Lenses
cs.IT cs.LG math.IT math.OC
It is hard to exaggerate the role of economic aggregators -- functions that summarize numerous and / or heterogeneous data -- in economic models since the early XX$^{th}$ century. In many cases, as witnessed by the pioneering works of Cobb and Douglas, these functions were information quantities tailored to economic theories, i.e. they were built to fit economic phenomena. In this paper, we look at these functions from the complementary side: information. We use a recent toolbox built on top of a vast class of distortions coined by Bregman, whose application field rivals metrics' in various subfields of mathematics. This toolbox makes it possible to find the quality of an aggregator (for consumptions, prices, labor, capital, wages, etc.), from the standpoint of the information it carries. We prove a rather striking result. From the informational standpoint, well-known economic aggregators do belong to the \textit{optimal} set. As common economic assumptions enter the analysis, this large set shrinks, and it essentially ends up \textit{exactly fitting} either CES, or Cobb-Douglas, or both. To summarize, in the relevant economic contexts, one could not have crafted better some aggregator from the information standpoint. We also discuss global economic behaviors of optimal information aggregators in general, and present a brief panorama of the links between economic and information aggregators. Keywords: Economic Aggregators, CES, Cobb-Douglas, Bregman divergences
0801.0426
On the Relationship between Transmission Power and Capacity of an Underwater Acoustic Communication Channel
cs.IT math.IT
The underwater acoustic channel is characterized by a path loss that depends not only on the transmission distance, but also on the signal frequency. As a consequence, transmission bandwidth depends on the transmission distance, a feature that distinguishes an underwater acoustic system from a terrestrial radio system. The exact relationship between power, transmission band, distance and capacity for the Gaussian noise scenario is a complicated one. This work provides a closed-form approximate model for 1) power consumption, 2) band-edge frequency and 3) bandwidth as functions of distance and capacity required for a data link. This approximate model is obtained by numerical evaluation of analytical results which takes into account physical models of acoustic propagation loss and ambient noise. The closed-form approximations may become useful tools in the design and analysis of underwater acoustic networks.
0801.0452
Sum Capacity of the Gaussian Interference Channel in the Low Interference Regime
cs.IT math.IT
New upper bounds on the sum capacity of the two-user Gaussian interference channel are derived. Using these bounds, it is shown that treating interference as noise achieves the sum capacity if the interference levels are below certain thresholds.
0801.0540
Blind decoding of Linear Gaussian channels with ISI, capacity, error exponent, universality
cs.IT math.IT
A new straightforward universal blind detection algorithm for linear Gaussian channel with ISI is given. A new error exponent is derived, which is better than Gallager's random coding error exponent.
0801.0581
Capacity of The Discrete-Time Non-Coherent Memoryless Rayleigh Fading Channels at Low SNR
cs.IT math.IT
The capacity of a discrete-time memoryless channel, in which successive symbols fade independently, and where the channel state information (CSI) is neither available at the transmitter nor at the receiver, is considered at low SNR. We derive a closed form expression of the optimal capacity-achieving input distribution at low signal-to-noise ratio (SNR) and give the exact capacity of a non-coherent channel at low SNR. The derived relations allow to better understanding the capacity of non-coherent channels at low SNR and bring an analytical answer to the peculiar behavior of the optimal input distribution observed in a previous work by Abou Faycal, Trott and Shamai. Then, we compute the non-coherence penalty and give a more precise characterization of the sub-linear term in SNR. Finally, in order to better understand how the optimal input varies with SNR, upper and lower bounds on the capacity-achieving input are given.
0801.0597
Distributed Power Allocation Strategies for Parallel Relay Networks
cs.IT math.IT
We consider a source-destination pair assisted by parallel regenerative decode-and-forward relays operating in orthogonal channels. We investigate distributed power allocation strategies for this system with limited channel state information at the source and the relay nodes. We first propose a distributed decision mechanism for each relay to individually make its decision on whether to forward the source data. The decision mechanism calls for each relay that is able to decode the information from the source to compare its relay-to-destination channel gain with a given threshold. We identify the optimum distributed power allocation strategy that minimizes the total transmit power while providing a target signal-to-noise ratio at the destination with a target outage probability. The strategy dictates the optimum choices for the source power as well as the threshold value at the relays. Next, we consider two simpler distributed power allocation strategies, namely the passive source model where the source power and the relay threshold are fixed, and the single relay model where only one relay is allowed to forward the source data. These models are motivated by limitations on the available channel state information as well as ease of implementation as compared to the optimum distributed strategy. Simulation results are presented to demonstrate the performance of the proposed distributed power allocation schemes. Specifically, we observe significant power savings with proposed methods as compared to random relay selection.
0801.0672
On Multipath Fading Channels at High SNR
cs.IT math.IT
This paper studies the capacity of discrete-time multipath fading channels. It is assumed that the number of paths is finite, i.e., that the channel output is influenced by the present and by the L previous channel inputs. A noncoherent channel model is considered where neither transmitter nor receiver are cognizant of the fading's realization, but both are aware of its statistic. The focus is on capacity at high signal-to-noise ratios (SNR). In particular, the capacity pre-loglog - defined as the limiting ratio of the capacity to loglog SNR as SNR tends to infinity - is studied. It is shown that, irrespective of the number paths L, the capacity pre-loglog is 1.
0801.0678
Implementation of perception and action at nanoscale
cs.RO cs.HC
Real time combination of nanosensors and nanoactuators with virtual reality environment and multisensorial interfaces enable us to efficiently act and perceive at nanoscale. Advanced manipulation of nanoobjects and new strategies for scientific education are the key motivations. We have no existing intuitive representation of the nanoworld ruled by laws foreign to our experience. A central challenge is then the construction of nanoworld simulacrum that we can start to visit and to explore. In this nanoworld simulacrum, object identifications will be based on probed entity physical and chemical intrinsic properties, on their interactions with sensors and on the final choices made in building a multisensorial interface so that these objects become coherent elements of the human sphere of action and perception. Here we describe a 1D virtual nanomanipulator, part of the Cit\'e des Sciences EXPO NANO in Paris, that is the first realization based on this program.
0801.0701
Adversarial Models and Resilient Schemes for Network Coding
cs.IT cs.DC cs.NI math.IT
In a recent paper, Jaggi et al. (INFOCOM 2007), presented a distributed polynomial-time rate-optimal network-coding scheme that works in the presence of Byzantine faults. We revisit their adversarial models and augment them with three, arguably realistic, models. In each of the models, we present a distributed scheme that demonstrates the usefulness of the model. In particular, all of the schemes obtain optimal rate $C-z$, where $C$ is the network capacity and $z$ is a bound on the number of links controlled by the adversary.
0801.0714
Regular Expression Subtyping for XML Query and Update Languages
cs.PL cs.DB
XML database query languages such as XQuery employ regular expression types with structural subtyping. Subtyping systems typically have two presentations, which should be equivalent: a declarative version in which the subsumption rule may be used anywhere, and an algorithmic version in which the use of subsumption is limited in order to make typechecking syntax-directed and decidable. However, the XQuery standard type system circumvents this issue by using imprecise typing rules for iteration constructs and defining only algorithmic typechecking, and another extant proposal provides more precise types for iteration constructs but ignores subtyping. In this paper, we consider a core XQuery-like language with a subsumption rule and prove the completeness of algorithmic typechecking; this is straightforward for XQuery proper but requires some care in the presence of more precise iteration typing disciplines. We extend this result to an XML update language we have introduced in earlier work.
0801.0756
Distributed Source Coding for Interactive Function Computation
cs.IT math.IT
A two-terminal interactive distributed source coding problem with alternating messages for function computation at both locations is studied. For any number of messages, a computable characterization of the rate region is provided in terms of single-letter information measures. While interaction is useless in terms of the minimum sum-rate for lossless source reproduction at one or both locations, the gains can be arbitrarily large for function computation even when the sources are independent. For a class of sources and functions, interaction is shown to be useless, even with infinite messages, when a function has to be computed at only one location, but is shown to be useful, if functions have to be computed at both locations. For computing the Boolean AND function of two independent Bernoulli sources at both locations, an achievable infinite-message sum-rate with infinitesimal-rate messages is derived in terms of a two-dimensional definite integral and a rate-allocation curve. A general framework for multiterminal interactive function computation based on an information exchange protocol which successively switches among different distributed source coding configurations is developed. For networks with a star topology, multiple rounds of interactive coding is shown to decrease the scaling law of the total network rate by an order of magnitude as the network grows.
0801.0815
Joint Wyner-Ziv/Dirty Paper coding by modulo-lattice modulation
cs.IT math.IT
The combination of source coding with decoder side-information (Wyner-Ziv problem) and channel coding with encoder side-information (Gel'fand-Pinsker problem) can be optimally solved using the separation principle. In this work we show an alternative scheme for the quadratic-Gaussian case, which merges source and channel coding. This scheme achieves the optimal performance by a applying modulo-lattice modulation to the analog source. Thus it saves the complexity of quantization and channel decoding, and remains with the task of "shaping" only. Furthermore, for high signal-to-noise ratio (SNR), the scheme approaches the optimal performance using an SNR-independent encoder, thus it is robust to unknown SNR at the encoder.
0801.0821
Unified Quantum Convolutional Coding
quant-ph cs.IT math.IT
We outline a quantum convolutional coding technique for protecting a stream of classical bits and qubits. Our goal is to provide a framework for designing codes that approach the ``grandfather'' capacity of an entanglement-assisted quantum channel for sending classical and quantum information simultaneously. Our method incorporates several resources for quantum redundancy: fresh ancilla qubits, entangled bits, and gauge qubits. The use of these diverse resources gives our technique the benefits of both active and passive quantum error correction. We can encode a classical-quantum bit stream with periodic quantum gates because our codes possess a convolutional structure. We end with an example of a ``grandfather'' quantum convolutional code that protects one qubit and one classical bit per frame by encoding them with one fresh ancilla qubit, one entangled bit, and one gauge qubit per frame. We explicitly provide the encoding and decoding circuits for this example.
0801.0830
Evolution of central pattern generators for the control of a five-link bipedal walking mechanism
cs.NE cs.RO
Central pattern generators (CPGs), with a basis is neurophysiological studies, are a type of neural network for the generation of rhythmic motion. While CPGs are being increasingly used in robot control, most applications are hand-tuned for a specific task and it is acknowledged in the field that generic methods and design principles for creating individual networks for a given task are lacking. This study presents an approach where the connectivity and oscillatory parameters of a CPG network are determined by an evolutionary algorithm with fitness evaluations in a realistic simulation with accurate physics. We apply this technique to a five-link planar walking mechanism to demonstrate its feasibility and performance. In addition, to see whether results from simulation can be acceptably transferred to real robot hardware, the best evolved CPG network is also tested on a real mechanism. Our results also confirm that the biologically inspired CPG model is well suited for legged locomotion, since a diverse manifestation of networks have been observed to succeed in fitness simulations during evolution.
0801.0841
Capacity of the Bosonic Wiretap Channel and the Entropy Photon-Number Inequality
quant-ph cs.IT math.IT
Determining the ultimate classical information carrying capacity of electromagnetic waves requires quantum-mechanical analysis to properly account for the bosonic nature of these waves. Recent work has established capacity theorems for bosonic single-user and broadcast channels, under the presumption of two minimum output entropy conjectures. Despite considerable accumulated evidence that supports the validity of these conjectures, they have yet to be proven. In this paper, it is shown that the second conjecture suffices to prove the classical capacity of the bosonic wiretap channel, which in turn would also prove the quantum capacity of the lossy bosonic channel. The preceding minimum output entropy conjectures are then shown to be simple consequences of an Entropy Photon-Number Inequality (EPnI), which is a conjectured quantum-mechanical analog of the Entropy Power Inequality (EPI) form classical information theory.
0801.0857
Period-Different $m$-Sequences With At Most A Four-Valued Cross Correlation
cs.IT cs.DM math.IT
In this paper, we follow the recent work of Helleseth, Kholosha, Johanssen and Ness to study the cross correlation between an $m$-sequence of period $2^m-1$ and the $d$-decimation of an $m$-sequence of shorter period $2^{n}-1$ for an even number $m=2n$. Assuming that $d$ satisfies $d(2^l+1)=2^i({\rm mod} 2^n-1)$ for some $l$ and $i$, we prove the cross correlation takes exactly either three or four values, depending on ${\rm gcd}(l,n)$ is equal to or larger than 1. The distribution of the correlation values is also completely determined. Our result confirms the numerical phenomenon Helleseth et al found. It is conjectured that there are no more other cases of $d$ that give at most a four-valued cross correlation apart from the ones proved here.
0801.0931
The Asymptotic Bit Error Probability of LDPC Codes for the Binary Erasure Channel with Finite Iteration Number
cs.IT math.IT
We consider communication over the binary erasure channel (BEC) using low-density parity-check (LDPC) code and belief propagation (BP) decoding. The bit error probability for infinite block length is known by density evolution and it is well known that a difference between the bit error probability at finite iteration number for finite block length $n$ and for infinite block length is asymptotically $\alpha/n$, where $\alpha$ is a specific constant depending on the degree distribution, the iteration number and the erasure probability. Our main result is to derive an efficient algorithm for calculating $\alpha$ for regular ensembles. The approximation using $\alpha$ is accurate for $(2,r)$-regular ensembles even in small block length.
0801.0938
Cognitive Networks Achieve Throughput Scaling of a Homogeneous Network
cs.IT math.IT
We study two distinct, but overlapping, networks that operate at the same time, space, and frequency. The first network consists of $n$ randomly distributed \emph{primary users}, which form either an ad hoc network, or an infrastructure-supported ad hoc network with $l$ additional base stations. The second network consists of $m$ randomly distributed, ad hoc secondary users or cognitive users. The primary users have priority access to the spectrum and do not need to change their communication protocol in the presence of secondary users. The secondary users, however, need to adjust their protocol based on knowledge about the locations of the primary nodes to bring little loss to the primary network's throughput. By introducing preservation regions around primary receivers and avoidance regions around primary base stations, we propose two modified multihop routing protocols for the cognitive users. Base on percolation theory, we show that when the secondary network is denser than the primary network, both networks can simultaneously achieve the same throughput scaling law as a stand-alone network. Furthermore, the primary network throughput is subject to only a vanishingly fractional loss. Specifically, for the ad hoc and the infrastructure-supported primary models, the primary network achieves sum throughputs of order $n^{1/2}$ and $\max\{n^{1/2},l\}$, respectively. For both primary network models, for any $\delta>0$, the secondary network can achieve sum throughput of order $m^{1/2-\delta}$ with an arbitrarily small fraction of outage. Thus, almost all secondary source-destination pairs can communicate at a rate of order $m^{-1/2-\delta}$.
0801.0969
Pareto and Boltzmann-Gibbs behaviors in a deterministic multi-agent system
q-fin.GN cond-mat.stat-mech cs.MA nlin.AO nlin.CD physics.comp-ph physics.soc-ph
A deterministic system of interacting agents is considered as a model for economic dynamics. The dynamics of the system is described by a coupled map lattice with near neighbor interactions. The evolution of each agent results from the competition between two factors: the agent's own tendency to grow and the environmental influence that moderates this growth. Depending on the values of the parameters that control these factors, the system can display Pareto or Boltzmann-Gibbs statistical behaviors in its asymptotic dynamical regime. The regions where these behaviors appear are calculated on the space of parameters of the system. Other statistical properties, such as the mean wealth, the standard deviation, and the Gini coefficient characterizing the degree of equity in the wealth distribution are also calculated on the space of parameters of the system.
0801.1002
Capacity Bounds for Peak-Constrained Multiantenna Wideband Channels
cs.IT math.IT
We derive bounds on the noncoherent capacity of a very general class of multiple-input multiple-output channels that allow for selectivity in time and frequency as well as for spatial correlation. The bounds apply to peak-constrained inputs; they are explicit in the channel's scattering function, are useful for a large range of bandwidth, and allow to coarsely identify the capacity-optimal combination of bandwidth and number of transmit antennas. Furthermore, we obtain a closed-form expression for the first-order Taylor series expansion of capacity in the limit of infinite bandwidth. From this expression, we conclude that in the wideband regime: (i) it is optimal to use only one transmit antenna when the channel is spatially uncorrelated; (ii) rank-one statistical beamforming is optimal if the channel is spatially correlated; and (iii) spatial correlation, be it at the transmitter, the receiver, or both, is beneficial.
0801.1060
On the Period of a Periodic-Finite-Type Shift
cs.IT math.IT
Periodic-finite-type shifts (PFT's) form a class of sofic shifts that strictly contains the class of shifts of finite type (SFT's). In this paper, we investigate how the notion of "period" inherent in the definition of a PFT causes it to differ from an SFT, and how the period influences the properties of a PFT.
0801.1063
Modeling Online Reviews with Multi-grain Topic Models
cs.IR cs.DB
In this paper we present a novel framework for extracting the ratable aspects of objects from online user reviews. Extracting such aspects is an important challenge in automatically mining product opinions from the web and in generating opinion-based summaries of user reviews. Our models are based on extensions to standard topic modeling methods such as LDA and PLSA to induce multi-grain topics. We argue that multi-grain models are more appropriate for our task since standard models tend to produce topics that correspond to global properties of objects (e.g., the brand of a product type) rather than the aspects of an object that tend to be rated by a user. The models we present not only extract ratable aspects, but also cluster them into coherent topics, e.g., `waitress' and `bartender' are part of the same topic `staff' for restaurants. This differentiates it from much of the previous work which extracts aspects through term frequency analysis with minimal clustering. We evaluate the multi-grain models both qualitatively and quantitatively to show that they improve significantly upon standard topic models.
0801.1067
The lowest-possible BER and FER for any discrete memoryless channel with given capacity
cs.IT math.IT
We investigate properties of a channel coding scheme leading to the minimum-possible frame error ratio when transmitting over a memoryless channel with rate R>C. The results are compared to the well-known properties of a channel coding scheme leading to minimum bit error ratio. It is concluded that these two optimization requests are contradicting. A valuable application of the derived results is presented.
0801.1126
Concave Programming Upper Bounds on the Capacity of 2-D Constraints
cs.IT math.IT
The capacity of 1-D constraints is given by the entropy of a corresponding stationary maxentropic Markov chain. Namely, the entropy is maximized over a set of probability distributions, which is defined by some linear requirements. In this paper, certain aspects of this characterization are extended to 2-D constraints. The result is a method for calculating an upper bound on the capacity of 2-D constraints. The key steps are: The maxentropic stationary probability distribution on square configurations is considered. A set of linear equalities and inequalities is derived from this stationarity. The result is a concave program, which can be easily solved numerically. Our method improves upon previous upper bounds for the capacity of the 2-D ``no independent bits'' constraint, as well as certain 2-D RLL constraints.
0801.1136
A Constrained Channel Coding Approach to Joint Communication and Channel Estimation
cs.IT math.IT
A joint communication and channel state estimation problem is investigated, in which reliable information transmission over a noisy channel, and high-fidelity estimation of the channel state, are simultaneously sought. The tradeoff between the achievable information rate and the estimation distortion is quantified by formulating the problem as a constrained channel coding problem, and the resulting capacity-distortion function characterizes the fundamental limit of the joint communication and channel estimation problem. The analytical results are illustrated through case studies, and further issues such as multiple cost constraints, channel uncertainty, and capacity per unit distortion are also briefly discussed.
0801.1138
An Addendum to "How Good is PSK for Peak-Limited Fading Channels in the Low-SNR Regime?"
cs.IT math.IT
A proof is provided of the operational achievability of $R_\mathrm{rt}$ by the recursive training scheme in \cite{zhang07:it}, for general wide-sense stationary and ergodic Rayleigh fading processes.
0801.1141
Coding Strategies for Noise-Free Relay Cascades with Half-Duplex Constraint
cs.IT math.IT
Two types of noise-free relay cascades are investigated. Networks where a source communicates with a distant receiver via a cascade of half-duplex constrained relays, and networks where not only the source but also a single relay node intends to transmit information to the same destination. We introduce two relay channel models, capturing the half-duplex constraint, and within the framework of these models capacity is determined for the first network type. It turns out that capacity is significantly higher than the rates which are achievable with a straightforward time-sharing approach. A capacity achieving coding strategy is presented based on allocating the transmit and receive time slots of a node in dependence of the node's previously received data. For the networks of the second type, an upper bound to the rate region is derived from the cut-set bound. Further, achievability of the cut-set bound in the single relay case is shown given that the source rate exceeds a certain minimum value.
0801.1179
Corpus sp{\'e}cialis{\'e} et ressource de sp{\'e}cialit{\'e}
cs.IR cs.CL
"Semantic Atlas" is a mathematic and statistic model to visualise word senses according to relations between words. The model, that has been applied to proximity relations from a corpus, has shown its ability to distinguish word senses as the corpus' contributors comprehend them. We propose to use the model and a specialised corpus in order to create automatically a specialised dictionary relative to the corpus' domain. A morpho-syntactic analysis performed on the corpus makes it possible to create the dictionary from syntactic relations between lexical units. The semantic resource can be used to navigate semantically - and not only lexically - through the corpus, to create classical dictionaries or for diachronic studies of the language.
0801.1185
Capacity of the Discrete-Time AWGN Channel Under Output Quantization
cs.IT math.IT
We investigate the limits of communication over the discrete-time Additive White Gaussian Noise (AWGN) channel, when the channel output is quantized using a small number of bits. We first provide a proof of our recent conjecture on the optimality of a discrete input distribution in this scenario. Specifically, we show that for any given output quantizer choice with K quantization bins (i.e., a precision of log2 K bits), the input distribution, under an average power constraint, need not have any more than K + 1 mass points to achieve the channel capacity. The cutting-plane algorithm is employed to compute this capacity and to generate optimum input distributions. Numerical optimization over the choice of the quantizer is then performed (for 2-bit and 3-bit symmetric quantization), and the results we obtain show that the loss due to low-precision output quantization, which is small at low signal-to-noise ratio (SNR) as expected, can be quite acceptable even for moderate to high SNR values. For example, at SNRs up to 20 dB, 2-3 bit quantization achieves 80-90% of the capacity achievable using infinite-precision quantization.
0801.1208
Hybrid Decoding of Finite Geometry LDPC Codes
cs.IT math.IT
For finite geometry low-density parity-check codes, heavy row and column weights in their parity check matrix make the decoding with even Min-Sum (MS) variants computationally expensive. To alleviate it, we present a class of hybrid schemes by concatenating a parallel bit flipping (BF) variant with an Min-Sum (MS) variant. In most SNR region of interest, without compromising performance or convergence rate, simulation results show that the proposed hybrid schemes can save substantial computational complexity with respect to MS variant decoding alone. Specifically, the BF variant, with much less computational complexity, bears most decoding load before resorting to MS variant. Computational and hardware complexity is also elaborated to justify the feasibility of the hybrid schemes.
0801.1275
Le terme et le concept : fondements d'une ontoterminologie
cs.AI
Most definitions of ontology, viewed as a "specification of a conceptualization", agree on the fact that if an ontology can take different forms, it necessarily includes a vocabulary of terms and some specification of their meaning in relation to the domain's conceptualization. And as domain knowledge is mainly conveyed through scientific and technical texts, we can hope to extract some useful information from them for building ontology. But is it as simple as this? In this article we shall see that the lexical structure, i.e. the network of words linked by linguistic relationships, does not necessarily match the domain conceptualization. We have to bear in mind that writing documents is the concern of textual linguistics, of which one of the principles is the incompleteness of text, whereas building ontology - viewed as task-independent knowledge - is concerned with conceptualization based on formal and not natural languages. Nevertheless, the famous Sapir and Whorf hypothesis, concerning the interdependence of thought and language, is also applicable to formal languages. This means that the way an ontology is built and a concept is defined depends directly on the formal language which is used; and the results will not be the same. The introduction of the notion of ontoterminology allows to take into account epistemological principles for formal ontology building.
0801.1276
On the guaranteed error correction capability of LDPC codes
cs.IT math.IT
We investigate the relation between the girth and the guaranteed error correction capability of $\gamma$-left regular LDPC codes when decoded using the bit flipping (serial and parallel) algorithms. A lower bound on the number of variable nodes which expand by a factor of at least $3 \gamma/4$ is found based on the Moore bound. An upper bound on the guaranteed correction capability is established by studying the sizes of smallest possible trapping sets.
0801.1282
LDPC Codes Which Can Correct Three Errors Under Iterative Decoding
cs.IT math.IT
In this paper, we provide necessary and sufficient conditions for a column-weight-three LDPC code to correct three errors when decoded using Gallager A algorithm. We then provide a construction technique which results in a code satisfying the above conditions. We also provide numerical assessment of code performance via simulation results.
0801.1306
Capacity Bounds for the Gaussian Interference Channel
cs.IT math.IT
The capacity region of the two-user Gaussian Interference Channel (IC) is studied. Three classes of channels are considered: weak, one-sided, and mixed Gaussian IC. For the weak Gaussian IC, a new outer bound on the capacity region is obtained that outperforms previously known outer bounds. The sum capacity for a certain range of channel parameters is derived. For this range, it is proved that using Gaussian codebooks and treating interference as noise is optimal. It is shown that when Gaussian codebooks are used, the full Han-Kobayashi achievable rate region can be obtained by using the naive Han-Kobayashi achievable scheme over three frequency bands (equivalently, three subspaces). For the one-sided Gaussian IC, an alternative proof for the Sato's outer bound is presented. We derive the full Han-Kobayashi achievable rate region when Gaussian codebooks are utilized. For the mixed Gaussian IC, a new outer bound is obtained that outperforms previously known outer bounds. For this case, the sum capacity for the entire range of channel parameters is derived. It is proved that the full Han-Kobayashi achievable rate region using Gaussian codebooks is equivalent to that of the one-sided Gaussian IC for a particular range of channel parameters.
0801.1336
Stream Computing
cs.AI
Stream computing is the use of multiple autonomic and parallel modules together with integrative processors at a higher level of abstraction to embody "intelligent" processing. The biological basis of this computing is sketched and the matter of learning is examined.
0801.1364
An Algorithm to Compute the Nearest Point in the Lattice $A_{n}^*$
cs.IT math.IT
The lattice $A_n^*$ is an important lattice because of its covering properties in low dimensions. Clarkson \cite{Clarkson1999:Anstar} described an algorithm to compute the nearest lattice point in $A_n^*$ that requires $O(n\log{n})$ arithmetic operations. In this paper, we describe a new algorithm. While the complexity is still $O(n\log{n})$, it is significantly simpler to describe and verify. In practice, we find that the new algorithm also runs faster.
0801.1415
The emerging field of language dynamics
cs.CL physics.soc-ph
A simple review by a linguist, citing many articles by physicists: Quantitative methods, agent-based computer simulations, language dynamics, language typology, historical linguistics
0801.1630
Computational Solutions for Today's Navy
cs.MA cs.GL
New methods are being employed to meet the Navy's changing software-development environment.
0801.1658
Computational approach to the emergence and evolution of language - evolutionary naming game model
physics.soc-ph cs.CL cs.MA
Computational modelling with multi-agent systems is becoming an important technique of studying language evolution. We present a brief introduction into this rapidly developing field, as well as our own contributions that include an analysis of the evolutionary naming-game model. In this model communicating agents, that try to establish a common vocabulary, 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 the model control parameter a poorly communicating group of linguistically unskilled agents transforms into almost perfectly communicating group with large learning abilities. 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. Under the assumption that communication intensity increases continuously with finite speed, the transition is split into several transition-like changes. It shows that the speed of cultural changes, that sets an additional characteristic timescale, might be yet another factor affecting the evolution of language. In our opinion, this model shows that linguistic and biological processes have a strong influence on each other and this effect certainly has contributed to an explosive development of our species.
0801.1703
The Quadratic Gaussian Rate-Distortion Function for Source Uncorrelated Distortions
cs.IT math.IT
We characterize the rate-distortion function for zero-mean stationary Gaussian sources under the MSE fidelity criterion and subject to the additional constraint that the distortion is uncorrelated to the input. The solution is given by two equations coupled through a single scalar parameter. This has a structure similar to the well known water-filling solution obtained without the uncorrelated distortion restriction. Our results fully characterize the unique statistics of the optimal distortion. We also show that, for all positive distortions, the minimum achievable rate subject to the uncorrelation constraint is strictly larger than that given by the un-constrained rate-distortion function. This gap increases with the distortion and tends to infinity and zero, respectively, as the distortion tends to zero and infinity.
0801.1715
On Breaching Enterprise Data Privacy Through Adversarial Information Fusion
cs.DB cs.CR cs.OH
Data privacy is one of the key challenges faced by enterprises today. Anonymization techniques address this problem by sanitizing sensitive data such that individual privacy is preserved while allowing enterprises to maintain and share sensitive data. However, existing work on this problem make inherent assumptions about the data that are impractical in day-to-day enterprise data management scenarios. Further, application of existing anonymization schemes on enterprise data could lead to adversarial attacks in which an intruder could use information fusion techniques to inflict a privacy breach. In this paper, we shed light on the shortcomings of current anonymization schemes in the context of enterprise data. We define and experimentally demonstrate Web-based Information- Fusion Attack on anonymized enterprise data. We formulate the problem of Fusion Resilient Enterprise Data Anonymization and propose a prototype solution to address this problem.
0801.1718
Achieving the Quadratic Gaussian Rate-Distortion Function for Source Uncorrelated Distortions
cs.IT math.IT
We prove achievability of the recently characterized quadratic Gaussian rate-distortion function (RDF) subject to the constraint that the distortion is uncorrelated to the source. This result is based on shaped dithered lattice quantization in the limit as the lattice dimension tends to infinity and holds for all positive distortions. It turns out that this uncorrelated distortion RDF can be realized causally. This feature, which stands in contrast to Shannon's RDF, is illustrated by causal transform coding. Moreover, we prove that by using feedback noise shaping the uncorrelated distortion RDF can be achieved causally and with memoryless entropy coding. Whilst achievability relies upon infinite dimensional quantizers, we prove that the rate loss incurred in the finite dimensional case can be upper-bounded by the space filling loss of the quantizer and, thus, is at most 0.254 bit/dimension.
0801.1736
A Central Limit Theorem for the SNR at the Wiener Filter Output for Large Dimensional Signals
cs.IT math.IT
Consider the quadratic form $\beta = {\bf y}^* ({\bf YY}^* + \rho {\bf I})^{-1} {\bf y}$ where $\rho$ is a positive number, where ${\bf y}$ is a random vector and ${\bf Y}$ is a $N \times K$ random matrix both having independent elements with different variances, and where ${\bf y}$ and ${\bf Y}$ are independent. Such quadratic forms represent the Signal to Noise Ratio at the output of the linear Wiener receiver for multi dimensional signals frequently encountered in wireless communications and in array processing. Using well known results of Random Matrix Theory, the quadratic form $\beta$ can be approximated with a known deterministic real number $\bar\beta_K$ in the asymptotic regime where $K\to\infty$ and $K/N \to \alpha > 0$. This paper addresses the problem of convergence of $\beta$. More specifically, it is shown here that $\sqrt{K}(\beta - \bar\beta_K)$ behaves for large $K$ like a Gaussian random variable which variance is provided.
0801.1883
D-optimal Bayesian Interrogation for Parameter and Noise Identification of Recurrent Neural Networks
cs.NE cs.IT math.IT
We introduce a novel online Bayesian method for the identification of a family of noisy recurrent neural networks (RNNs). We develop Bayesian active learning technique in order to optimize the interrogating stimuli given past experiences. In particular, we consider the unknown parameters as stochastic variables and use the D-optimality principle, also known as `\emph{infomax method}', to choose optimal stimuli. We apply a greedy technique to maximize the information gain concerning network parameters at each time step. We also derive the D-optimal estimation of the additive noise that perturbs the dynamical system of the RNN. Our analytical results are approximation-free. The analytic derivation gives rise to attractive quadratic update rules.
0801.1988
Online variants of the cross-entropy method
cs.LG
The cross-entropy method is a simple but efficient method for global optimization. In this paper we provide two online variants of the basic CEM, together with a proof of convergence.
0801.2034
On the Boundedness of the Support of Optimal Input Measures for Rayleigh Fading Channels
cs.IT math.IT
We consider transmission over a wireless multiple antenna communication system operating in a Rayleigh flat fading environment with no channel state information at the receiver and the transmitter with coherence time T=1. We show that, subject to the average power constraint, the support of the capacity achieving input distribution is bounded. Moreover, we show by a simple example concerning the identity theorem (or uniqueness theorem) from the complex analysis in several variables that some of the existing results in the field are not rigorous.
0801.2069
Factored Value Iteration Converges
cs.AI cs.LG
In this paper we propose a novel algorithm, factored value iteration (FVI), for the approximate solution of factored Markov decision processes (fMDPs). The traditional approximate value iteration algorithm is modified in two ways. For one, the least-squares projection operator is modified so that it does not increase max-norm, and thus preserves convergence. The other modification is that we uniformly sample polynomially many samples from the (exponentially large) state space. This way, the complexity of our algorithm becomes polynomial in the size of the fMDP description length. We prove that the algorithm is convergent. We also derive an upper bound on the difference between our approximate solution and the optimal one, and also on the error introduced by sampling. We analyze various projection operators with respect to their computation complexity and their convergence when combined with approximate value iteration.
0801.2088
Persistence of Wandering Intervals in Self-Similar Affine Interval Exchange Transformations
math.DS cs.IT math.IT
In this article we prove that given a self-similar interval exchange transformation T, whose associated matrix verifies a quite general algebraic condition, there exists an affine interval exchange transformation with wandering intervals that is semi-conjugated to it. That is, in this context the existence of Denjoy counterexamples occurs very often, generalizing the result of M. Cobo in [C].
0801.2144
Non-Additive Quantum Codes from Goethals and Preparata Codes
quant-ph cs.IT math.IT
We extend the stabilizer formalism to a class of non-additive quantum codes which are constructed from non-linear classical codes. As an example, we present infinite families of non-additive codes which are derived from Goethals and Preparata codes.
0801.2150
Quantum Goethals-Preparata Codes
quant-ph cs.IT math.IT
We present a family of non-additive quantum codes based on Goethals and Preparata codes with parameters ((2^m,2^{2^m-5m+1},8)). The dimension of these codes is eight times higher than the dimension of the best known additive quantum codes of equal length and minimum distance.
0801.2185
New Outer Bounds on the Capacity Region of Gaussian Interference Channels
cs.IT math.IT
Recent outer bounds on the capacity region of Gaussian interference channels are generalized to $m$-user channels with $m>2$ and asymmetric powers and crosstalk coefficients. The bounds are again shown to give the sum-rate capacity for Gaussian interference channels with low powers and crosstalk coefficients. The capacity is achieved by using single-user detection at each receiver, i.e., treating the interference as noise incurs no loss in performance.
0801.2233
Analysis of Non-binary Hybrid LDPC Codes
cs.IT math.IT
In this paper, we analyse asymptotically a new class of LDPC codes called Non-binary Hybrid LDPC codes, which has been recently introduced. We use density evolution techniques to derive a stability condition for hybrid LDPC codes, and prove their threshold behavior. We study this stability condition to conclude on asymptotic advantages of hybrid LDPC codes compared to their non-hybrid counterparts.
0801.2242
Information Spectrum Approach to Second-Order Coding Rate in Channel Coding
cs.IT math.IT
Second-order coding rate of channel coding is discussed for general sequence of channels. The optimum second-order transmission rate with a constant error constraint $\epsilon$ is obtained by using the information spectrum method. We apply this result to the discrete memoryless case, the discrete memoryless case with a cost constraint, the additive Markovian case, and the Gaussian channel case with an energy constraint. We also clarify that the Gallager bound does not give the optimum evaluation in the second-order coding rate.
0801.2323
Decentralized Two-Hop Opportunistic Relaying With Limited Channel State Information
cs.IT math.IT
A network consisting of $n$ source-destination pairs and $m$ relays is considered. Focusing on the large system limit (large $n$), the throughput scaling laws of two-hop relaying protocols are studied for Rayleigh fading channels. It is shown that, under the practical constraints of single-user encoding-decoding scheme, and partial channel state information (CSI) at the transmitters (via integer-value feedback from the receivers), the maximal throughput scales as $\log n$ even if full relay cooperation is allowed. Furthermore, a novel decentralized opportunistic relaying scheme with receiver CSI, partial transmitter CSI, and no relay cooperation, is shown to achieve the optimal throughput scaling law of $\log n$.
0801.2378
String algorithms and data structures
cs.DS cs.IR
The string-matching field has grown at a such complicated stage that various issues come into play when studying it: data structure and algorithmic design, database principles, compression techniques, architectural features, cache and prefetching policies. The expertise nowadays required to design good string data structures and algorithms is therefore transversal to many computer science fields and much more study on the orchestration of known, or novel, techniques is needed to make progress in this fascinating topic. This survey is aimed at illustrating the key ideas which should constitute, in our opinion, the current background of every index designer. We also discuss the positive features and drawback of known indexing schemes and algorithms, and devote much attention to detail research issues and open problems both on the theoretical and the experimental side.
0801.2398
Removing the Stiffness of Elastic Force from the Immersed Boundary Method for the 2D Stokes Equations
cs.CE cs.NA math.NA
The Immersed Boundary method has evolved into one of the most useful computational methods in studying fluid structure interaction. On the other hand, the Immersed Boundary method is also known to suffer from a severe timestep stability restriction when using an explicit time discretization. In this paper, we propose several efficient semi-implicit schemes to remove this stiffness from the Immersed Boundary method for the two-dimensional Stokes flow. First, we obtain a novel unconditionally stable semi-implicit discretization for the immersed boundary problem. Using this unconditionally stable discretization as a building block, we derive several efficient semi-implicit schemes for the immersed boundary problem by applying the Small Scale Decomposition to this unconditionally stable discretization. Our stability analysis and extensive numerical experiments show that our semi-implicit schemes offer much better stability property than the explicit scheme. Unlike other implicit or semi-implicit schemes proposed in the literature, our semi-implicit schemes can be solved explicitly in the spectral space. Thus the computational cost of our semi-implicit schemes is comparable to that of an explicit scheme, but with a much better stability property.
0801.2423
Design and Analysis of LDGM-Based Codes for MSE Quantization
cs.IT math.IT
Approaching the 1.5329-dB shaping (granular) gain limit in mean-squared error (MSE) quantization of R^n is important in a number of problems, notably dirty-paper coding. For this purpose, we start with a binary low-density generator-matrix (LDGM) code, and construct the quantization codebook by periodically repeating its set of binary codewords, or them mapped to m-ary ones with Gray mapping. The quantization algorithm is based on belief propagation, and it uses a decimation procedure to do the guessing necessary for convergence. Using the results of a true typical decimator (TTD) as reference, it is shown that the asymptotic performance of the proposed quantizer can be characterized by certain monotonicity conditions on the code's fixed point properties, which can be analyzed with density evolution, and degree distribution optimization can be carried out accordingly. When the number of iterations is finite, the resulting loss is made amenable to analysis through the introduction of a recovery algorithm from ``bad'' guesses, and the results of such analysis enable further optimization of the pace of decimation and the degree distribution. Simulation results show that the proposed LDGM-based quantizer can achieve a shaping gain of 1.4906 dB, or 0.0423 dB from the limit, and significantly outperforms trellis-coded quantization (TCQ) at a similar computational complexity.
0801.2480
Asynchronous Iterative Waterfilling for Gaussian Frequency-Selective Interference Channels
cs.IT cs.GT math.IT
This paper considers the maximization of information rates for the Gaussian frequency-selective interference channel, subject to power and spectral mask constraints on each link. To derive decentralized solutions that do not require any cooperation among the users, the optimization problem is formulated as a static noncooperative game of complete information. To achieve the so-called Nash equilibria of the game, we propose a new distributed algorithm called asynchronous iterative waterfilling algorithm. In this algorithm, the users update their power spectral density in a completely distributed and asynchronous way: some users may update their power allocation more frequently than others and they may even use outdated measurements of the received interference. The proposed algorithm represents a unified framework that encompasses and generalizes all known iterative waterfilling algorithms, e.g., sequential and simultaneous versions. The main result of the paper consists of a unified set of conditions that guarantee the global converge of the proposed algorithm to the (unique) Nash equilibrium of the game.
0801.2510
A Comparison of natural (english) and artificial (esperanto) languages. A Multifractal method based analysis
cs.CL physics.data-an
We present a comparison of two english texts, written by Lewis Carroll, one (Alice in wonderland) and the other (Through a looking glass), the former translated into esperanto, in order to observe whether natural and artificial languages significantly differ from each other. We construct one dimensional time series like signals using either word lengths or word frequencies. We use the multifractal ideas for sorting out correlations in the writings. In order to check the robustness of the methods we also write the corresponding shuffled texts. We compare characteristic functions and e.g. observe marked differences in the (far from parabolic) f(alpha) curves, differences which we attribute to Tsallis non extensive statistical features in the ''frequency time series'' and ''length time series''. The esperanto text has more extreme vallues. A very rough approximation consists in modeling the texts as a random Cantor set if resulting from a binomial cascade of long and short words (or words and blanks). This leads to parameters characterizing the text style, and most likely in fine the author writings.
0801.2588
Coding and Decoding for the Dynamic Decode and Forward Relay Protocol
cs.IT math.IT
We study the Dynamic Decode and Forward (DDF) protocol for a single half-duplex relay, single-antenna channel with quasi-static fading. The DDF protocol is well-known and has been analyzed in terms of the Diversity-Multiplexing Tradeoff (DMT) in the infinite block length limit. We characterize the finite block length DMT and give new explicit code constructions. The finite block length analysis illuminates a few key aspects that have been neglected in the previous literature: 1) we show that one dominating cause of degradation with respect to the infinite block length regime is the event of decoding error at the relay; 2) we explicitly take into account the fact that the destination does not generally know a priori the relay decision time at which the relay switches from listening to transmit mode. Both the above problems can be tackled by a careful design of the decoding algorithm. In particular, we introduce a decision rejection criterion at the relay based on Forney's decision rule (a variant of the Neyman-Pearson rule), such that the relay triggers transmission only when its decision is reliable. Also, we show that a receiver based on the Generalized Likelihood Ratio Test rule that jointly decodes the relay decision time and the information message achieves the optimal DMT. Our results show that no cyclic redundancy check (CRC) for error detection or additional protocol overhead to communicate the decision time are needed for DDF. Finally, we investigate the use of minimum mean squared error generalized decision feedback equalizer (MMSE-GDFE) lattice decoding at both the relay and the destination, and show that it provides near optimal performance at moderate complexity.
0801.2618
Survey of Technologies for Web Application Development
cs.SE cs.IR cs.NI
Web-based application developers face a dizzying array of platforms, languages, frameworks and technical artifacts to choose from. We survey, classify, and compare technologies supporting Web application development. The classification is based on (1) foundational technologies; (2)integration with other information sources; and (3) dynamic content generation. We further survey and classify software engineering techniques and tools that have been adopted from traditional programming into Web programming. We conclude that, although the infrastructure problems of the Web have largely been solved, the cacophony of technologies for Web-based applications reflects the lack of a solid model tailored for this domain.
0801.3024
Construction of Z4-linear Reed-Muller codes
cs.IT math.IT
New quaternary Plotkin constructions are given and are used to obtain new families of quaternary codes. The parameters of the obtained codes, such as the length, the dimension and the minimum distance are studied. Using these constructions new families of quaternary Reed-Muller codes are built with the peculiarity that after using the Gray map the obtained Z4-linear codes have the same parameters and fundamental properties as the codes in the usual binary linear Reed-Muller family. To make more evident the duality relationships in the constructed families the concept of Kronecker inner product is introduced.
0801.3042
Performance Analysis of a Cross-layer Collaborative Beamforming Approach in the Presence of Channel and Phase Errors
cs.IT math.IT
Collaborative beamforming enables nodes in a wireless network to transmit a common message over long distances in an energy efficient fashion. However, the process of making available the same message to all collaborating nodes introduces delays. The authors recently proposed a MAC-PHY cross-layer scheme that enables collaborative beamforming with significantly reduced collaboration overhead. The method requires knowledge of node locations and internode channel coefficients. In this paper, the performance of that approach is studied analytically in terms of average beampattern and symbol error probability (SEP) under realistic conditions, i.e., when imperfect channel estimates are used and when there are phase errors in the contributions of the collaborating nodes at the receiver.
0801.3046
A model for reactive porous transport during re-wetting of hardened concrete
cs.CE physics.flu-dyn
A mathematical model is developed that captures the transport of liquid water in hardened concrete, as well as the chemical reactions that occur between the imbibed water and the residual calcium silicate compounds residing in the porous concrete matrix. The main hypothesis in this model is that the reaction product -- calcium silicate hydrate gel -- clogs the pores within the concrete thereby hindering water transport. Numerical simulations are employed to determine the sensitivity of the model solution to changes in various physical parameters, and compare to experimental results available in the literature.
0801.3048
Human Heuristics for Autonomous Agents
cs.MA cs.HC cs.NI
We investigate the problem of autonomous agents processing pieces of information that may be corrupted (tainted). Agents have the option of contacting a central database for a reliable check of the status of the message, but this procedure is costly and therefore should be used with parsimony. Agents have to evaluate the risk of being infected, and decide if and when communicating partners are affordable. Trustability is implemented as a personal (one-to-one) record of past contacts among agents, and as a mean-field monitoring of the level of message corruption. Moreover, this information is slowly forgotten in time, so that at the end everybody is checked against the database. We explore the behavior of a homogeneous system in the case of a fixed pool of spreaders of corrupted messages, and in the case of spontaneous appearance of corrupted messages.
0801.3049
Spatial-Spectral Joint Detection for Wideband Spectrum Sensing in Cognitive Radio Networks
cs.IT math.IT
Spectrum sensing is an essential functionality that enables cognitive radios to detect spectral holes and opportunistically use under-utilized frequency bands without causing harmful interference to primary networks. Since individual cognitive radios might not be able to reliably detect weak primary signals due to channel fading/shadowing, this paper proposes a cooperative wideband spectrum sensing scheme, referred to as spatial-spectral joint detection, which is based on a linear combination of the local statistics from spatially distributed multiple cognitive radios. The cooperative sensing problem is formulated into an optimization problem, for which suboptimal but efficient solutions can be obtained through mathematical transformation under practical conditions.
0801.3073
Large Deviations Analysis for the Detection of 2D Hidden Gauss-Markov Random Fields Using Sensor Networks
cs.IT math.IT
The detection of hidden two-dimensional Gauss-Markov random fields using sensor networks is considered. Under a conditional autoregressive model, the error exponent for the Neyman-Pearson detector satisfying a fixed level constraint is obtained using the large deviations principle. For a symmetric first order autoregressive model, the error exponent is given explicitly in terms of the SNR and an edge dependence factor (field correlation). The behavior of the error exponent as a function of correlation strength is seen to divide into two regions depending on the value of the SNR. At high SNR, uncorrelated observations maximize the error exponent for a given SNR, whereas there is non-zero optimal correlation at low SNR. Based on the error exponent, the energy efficiency (defined as the ratio of the total information gathered to the total energy required) of ad hoc sensor network for detection is examined for two sensor deployment models: an infinite area model and and infinite density model. For a fixed sensor density, the energy efficiency diminishes to zero at rate O(area^{-1/2}) as the area is increased. On the other hand, non-zero efficiency is possible for increasing density depending on the behavior of the physical correlation as a function of the link length.
0801.3097
Auction-based Resource Allocation for Multi-relay Asynchronous Cooperative Networks
cs.IT math.IT
Resource allocation is considered for cooperative transmissions in multiple-relay wireless networks. Two auction mechanisms, SNR auctions and power auctions, are proposed to distributively coordinate the allocation of power among multiple relays. In the SNR auction, a user chooses the relay with the lowest weighted price. In the power auction, a user may choose to use multiple relays simultaneously, depending on the network topology and the relays' prices. Sufficient conditions for the existence (in both auctions) and uniqueness (in the SNR auction) of the Nash equilibrium are given. The fairness of the SNR auction and efficiency of the power auction are further discussed. It is also proven that users can achieve the unique Nash equilibrium distributively via best response updates in a completely asynchronous manner.
0801.3102
Balancing transparency, efficiency and security in pervasive systems
cs.HC cs.IR
This chapter will survey pervasive computing with a look at how its constraint for transparency affects issues of resource management and security. The goal of pervasive computing is to render computing transparent, such that computing resources are ubiquitously offered to the user and services are proactively performed for a user without his or her intervention. The task of integrating computing infrastructure into everyday life without making it excessively invasive brings about tradeoffs between flexibility and robustness, efficiency and effectiveness, as well as autonomy and reliability. As the feasibility of ubiquitous computing and its real potential for mass applications are still a matter of controversy, this chapter will look into the underlying issues of resource management and authentication to discover how these can be handled in a least invasive fashion. The discussion will be closed by an overview of the solutions proposed by current pervasive computing efforts, both in the area of generic platforms and for dedicated applications such as pervasive education and healthcare.
0801.3111
Analysis of Estimation of Distribution Algorithms and Genetic Algorithms on NK Landscapes
cs.NE cs.AI
This study analyzes performance of several genetic and evolutionary algorithms on randomly generated NK fitness landscapes with various values of n and k. A large number of NK problem instances are first generated for each n and k, and the global optimum of each instance is obtained using the branch-and-bound algorithm. Next, the hierarchical Bayesian optimization algorithm (hBOA), the univariate marginal distribution algorithm (UMDA), and the simple genetic algorithm (GA) with uniform and two-point crossover operators are applied to all generated instances. Performance of all algorithms is then analyzed and compared, and the results are discussed.
0801.3112
The Two User Gaussian Compound Interference Channel
cs.IT math.IT
We introduce the two user finite state compound Gaussian interference channel and characterize its capacity region to within one bit. The main contributions involve both novel inner and outer bounds. The inner bound is multilevel superposition coding, but the decoding of the levels is opportunistic, depending on the channel state. The genie aided outer bound is motivated by the typical error events of the achievable scheme.
0801.3113
iBOA: The Incremental Bayesian Optimization Algorithm
cs.NE cs.AI
This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of the Bayesian network. iBOA is shown to be able to learn and exploit unrestricted Bayesian networks using incremental techniques for updating both the structure as well as the parameters of the probabilistic model. This represents an important step toward the design of competent incremental estimation of distribution algorithms that can solve difficult nearly decomposable problems scalably and reliably.
0801.3147
From k-SAT to k-CSP: Two Generalized Algorithms
cs.DS cs.AI cs.CC
Constraint satisfaction problems (CSPs) models many important intractable NP-hard problems such as propositional satisfiability problem (SAT). Algorithms with non-trivial upper bounds on running time for restricted SAT with bounded clause length k (k-SAT) can be classified into three styles: DPLL-like, PPSZ-like and Local Search, with local search algorithms having already been generalized to CSP with bounded constraint arity k (k-CSP). We generalize a DPLL-like algorithm in its simplest form and a PPSZ-like algorithm from k-SAT to k-CSP. As far as we know, this is the first attempt to use PPSZ-like strategy to solve k-CSP, and before little work has been focused on the DPLL-like or PPSZ-like strategies for k-CSP.
0801.3199
Descent methods for Nonnegative Matrix Factorization
cs.NA cs.IR math.OC
In this paper, we present several descent methods that can be applied to nonnegative matrix factorization and we analyze a recently developped fast block coordinate method called Rank-one Residue Iteration (RRI). We also give a comparison of these different methods and show that the new block coordinate method has better properties in terms of approximation error and complexity. By interpreting this method as a rank-one approximation of the residue matrix, we prove that it \emph{converges} and also extend it to the nonnegative tensor factorization and introduce some variants of the method by imposing some additional controllable constraints such as: sparsity, discreteness and smoothness.
0801.3209
A Pyramidal Evolutionary Algorithm with Different Inter-Agent Partnering Strategies for Scheduling Problems
cs.NE cs.CE
This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.
0801.3239
Online-concordance "Perekhresni stezhky" ("The Cross-Paths"), a novel by Ivan Franko
cs.CL cs.DL
In the article, theoretical principles and practical realization for the compilation of the concordance to "Perekhresni stezhky" ("The Cross-Paths"), a novel by Ivan Franko, are described. Two forms for the context presentation are proposed. The electronic version of this lexicographic work is available online.
0801.3272
Nonregenerative MIMO Relaying with Optimal Transmit Antenna Selection
cs.IT math.IT
We derive optimal SNR-based transmit antenna selection rules at the source and relay for the nonregenerative half duplex MIMO relay channel. While antenna selection is a suboptimal form of beamforming, it has the advantage that the optimization is tractable and can be implemented with only a few bits of feedback from the destination to the source and relay. We compare the bit error rate of optimal antenna selection at both the source and relay to other proposed beamforming techniques and propose methods for performing the necessary limited feedback.
0801.3289
Optimal Medium Access Control in Cognitive Radios: A Sequential Design Approach
cs.IT cs.NI math.IT
The design of medium access control protocols for a cognitive user wishing to opportunistically exploit frequency bands within parts of the radio spectrum having multiple bands is considered. In the scenario under consideration, the availability probability of each channel is unknown a priori to the cognitive user. Hence efficient medium access strategies must strike a balance between exploring the availability of channels and exploiting the opportunities identified thus far. Using a sequential design approach, an optimal medium access strategy is derived. To avoid the prohibitive computational complexity of this optimal strategy, a low complexity asymptotically optimal strategy is also developed. The proposed strategy does not require any prior statistical knowledge about the traffic pattern on the different channels.
0801.3511
Deterministic Design of Low-Density Parity-Check Codes for Binary Erasure Channels
cs.IT math.IT
We propose a deterministic method to design irregular Low-Density Parity-Check (LDPC) codes for binary erasure channels (BEC). Compared to the existing methods, which are based on the application of asymptomatic analysis tools such as density evolution or Extrinsic Information Transfer (EXIT) charts in an optimization process, the proposed method is much simpler and faster. Through a number of examples, we demonstrate that the codes designed by the proposed method perform very closely to the best codes designed by optimization. An important property of the proposed designs is the flexibility to select the number of constituent variable node degrees P. The proposed designs include existing deterministic designs as a special case with P = N-1, where N is the maximum variable node degree. Compared to the existing deterministic designs, for a given rate and a given d > 0, the designed ensembles can have a threshold in d-neighborhood of the capacity upper bound with smaller values of P and N. They can also achieve the capacity of the BEC as N, and correspondingly P and the maximum check node degree tend to infinity.
0801.3521
Capacity of Sparse Wideband Channels with Partial Channel Feedback
cs.IT math.IT
This paper studies the ergodic capacity of wideband multipath channels with limited feedback. Our work builds on recent results that have established the possibility of significant capacity gains in the wideband/low-SNR regime when there is perfect channel state information (CSI) at the transmitter. Furthermore, the perfect CSI benchmark gain can be obtained with the feedback of just one bit per channel coefficient. However, the input signals used in these methods are peaky, that is, they have a large peak-to-average power ratios. Signal peakiness is related to channel coherence and many recent measurement campaigns show that, in contrast to previous assumptions, wideband channels exhibit a sparse multipath structure that naturally leads to coherence in time and frequency. In this work, we first show that even an instantaneous power constraint is sufficient to achieve the benchmark gain when perfect CSI is available at the receiver. In the more realistic non-coherent setting, we study the performance of a training-based signaling scheme. We show that multipath sparsity can be leveraged to achieve the benchmark gain under both average as well as instantaneous power constraints as long as the channel coherence scales at a sufficiently fast rate with signal space dimensions. We also present rules of thumb on choosing signaling parameters as a function of the channel parameters so that the full benefits of sparsity can be realized.
0801.3526
Quantized Multimode Precoding in Spatially Correlated Multi-Antenna Channels
cs.IT math.IT
Multimode precoding, where the number of independent data-streams is adapted optimally, can be used to maximize the achievable throughput in multi-antenna communication systems. Motivated by standardization efforts embraced by the industry, the focus of this work is on systematic precoder design with realistic assumptions on the spatial correlation, channel state information (CSI) at the transmitter and the receiver, and implementation complexity. For spatial correlation of the channel matrix, we assume a general channel model, based on physical principles, that has been verified by many recent measurement campaigns. We also assume a coherent receiver and knowledge of the spatial statistics at the transmitter along with the presence of an ideal, low-rate feedback link from the receiver to the transmitter. The reverse link is used for codebook-index feedback and the goal of this work is to construct precoder codebooks, adaptable in response to the statistical information, such that the achievable throughput is significantly enhanced over that of a fixed, non-adaptive, i.i.d. codebook design. We illustrate how a codebook of semiunitary precoder matrices localized around some fixed center on the Grassmann manifold can be skewed in response to the spatial correlation via low-complexity maps that can rotate and scale submanifolds on the Grassmann manifold. The skewed codebook in combination with a lowcomplexity statistical power allocation scheme is then shown to bridge the gap in performance between a perfect CSI benchmark and an i.i.d. codebook design.
0801.3539
On the Effects of Idiotypic Interactions for Recommendation Communities in Artificial Immune Systems
cs.NE cs.AI
It has previously been shown that a recommender based on immune system idiotypic principles can out perform one based on correlation alone. This paper reports the results of work in progress, where we undertake some investigations into the nature of this beneficial effect. The initial findings are that the immune system recommender tends to produce different neighbourhoods, and that the superior performance of this recommender is due partly to the different neighbourhoods, and partly to the way that the idiotypic effect is used to weight each neighbours recommendations.
0801.3547
A Recommender System based on the Immune Network
cs.NE cs.AI
The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an artificial immune system (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by collaborative filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen - antibody interaction for matching and antibody - antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.
0801.3549
The Danger Theory and Its Application to Artificial Immune Systems
cs.NE cs.AI cs.CR
Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for Artificial Immune Systems.
0801.3550
Partnering Strategies for Fitness Evaluation in a Pyramidal Evolutionary Algorithm
cs.NE cs.AI
This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes for (sub-)fitness evaluation purposes are examined for two multiple-choice optimisation problems. It is shown that random partnering strategies perform best by providing better sampling and more diversity.
0801.3640
Energy Efficiency in Multi-Hop CDMA Networks: a Game Theoretic Analysis Considering Operating Costs
cs.IT math.IT
A game-theoretic analysis is used to study the effects of receiver choice and transmit power on the energy efficiency of multi-hop networks in which the nodes communicate using Direct-Sequence Code Division Multiple Access (DS-CDMA). A Nash equilibrium of the game in which the network nodes can choose their receivers as well as their transmit powers to maximize the total number of bits they transmit per unit of energy spent (including both transmit and operating energy) is derived. The energy efficiencies resulting from the use of different linear multiuser receivers in this context are compared for the non-cooperative game. Significant gains in energy efficiency are observed when multiuser receivers, particularly the linear minimum mean-square error (MMSE) receiver, are used instead of conventional matched filter receivers.
0801.3654
A path following algorithm for the graph matching problem
cs.CV cs.DM
We propose a convex-concave programming approach for the labeled weighted graph matching problem. The convex-concave programming formulation is obtained by rewriting the weighted graph matching problem as a least-square problem on the set of permutation matrices and relaxing it to two different optimization problems: a quadratic convex and a quadratic concave optimization problem on the set of doubly stochastic matrices. The concave relaxation has the same global minimum as the initial graph matching problem, but the search for its global minimum is also a hard combinatorial problem. We therefore construct an approximation of the concave problem solution by following a solution path of a convex-concave problem obtained by linear interpolation of the convex and concave formulations, starting from the convex relaxation. This method allows to easily integrate the information on graph label similarities into the optimization problem, and therefore to perform labeled weighted graph matching. The algorithm is compared with some of the best performing graph matching methods on four datasets: simulated graphs, QAPLib, retina vessel images and handwritten chinese characters. In all cases, the results are competitive with the state-of-the-art.
0801.3702
Joint source and channel coding for MIMO systems: Is it better to be robust or quick?
cs.IT math.IT
We develop a framework to optimize the tradeoff between diversity, multiplexing, and delay in MIMO systems to minimize end-to-end distortion. We first focus on the diversity-multiplexing tradeoff in MIMO systems, and develop analytical results to minimize distortion of a vector quantizer concatenated with a space-time MIMO channel code. In the high SNR regime we obtain a closed-form expression for the end-to-end distortion as a function of the optimal point on the diversity-multiplexing tradeoff curve. For large but finite SNR we find this optimal point via convex optimization. We then consider MIMO systems using ARQ retransmission to provide additional diversity at the expense of delay. For sources without a delay constraint, distortion is minimized by maximizing the ARQ window size. This results in an ARQ-enhanced multiplexing-diversity tradeoff region, with distortion minimized over this region in the same manner as without ARQ. Under a source delay constraint the problem formulation changes to account for delay distortion associated with random message arrival and random ARQ completion times. We use a dynamic programming formulation to capture the channel diversity-multiplexing tradeoff at finite SNR as well as the random arrival and retransmission dynamics; we solve for the optimal multiplexing-diversity-delay tradeoff to minimize end-to-end distortion associated with the source encoder, channel, and ARQ retransmissions. Our results show that a delay-sensitive system should adapt its operating point on the diversity-multiplexing-delay tradeoff region to the system dynamics. We provide numerical results that demonstrate significant performance gains of this adaptive policy over a static allocation of diversity/multiplexing in the channel code and a static ARQ window size.