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cs/0506089
Field geology with a wearable computer: 1st results of the Cyborg Astrobiologist System
cs.CV astro-ph cs.AI cs.CE cs.HC cs.RO
We present results from the first geological field tests of the `Cyborg Astrobiologist', which is a wearable computer and video camcorder system that we are using to test and train a computer-vision system towards having some of the autonomous decision-making capabilities of a field-geologist. The Cyborg Astrobiologist platform has thus far been used for testing and development of these algorithms and systems: robotic acquisition of quasi-mosaics of images, real-time image segmentation, and real-time determination of interesting points in the image mosaics. This work is more of a test of the whole system, rather than of any one part of the system. However, beyond the concept of the system itself, the uncommon map (despite its simplicity) is the main innovative part of the system. The uncommon map helps to determine interest-points in a context-free manner. Overall, the hardware and software systems function reliably, and the computer-vision algorithms are adequate for the first field tests. In addition to the proof-of-concept aspect of these field tests, the main result of these field tests is the enumeration of those issues that we can improve in the future, including: dealing with structural shadow and microtexture, and also, controlling the camera's zoom lens in an intelligent manner. Nonetheless, despite these and other technical inadequacies, this Cyborg Astrobiologist system, consisting of a camera-equipped wearable-computer and its computer-vision algorithms, has demonstrated its ability of finding genuinely interesting points in real-time in the geological scenery, and then gathering more information about these interest points in an automated manner. We use these capabilities for autonomous guidance towards geological points-of-interest.
cs/0506091
A New Construction for LDPC Codes using Permutation Polynomials over Integer Rings
cs.IT math.IT
A new construction is proposed for low density parity check (LDPC) codes using quadratic permutation polynomials over finite integer rings. The associated graphs for the new codes have both algebraic and pseudo-random nature, and the new codes are quasi-cyclic. Graph isomorphisms and automorphisms are identified and used in an efficient search for good codes. Graphs with girth as large as 12 were found. Upper bounds on the minimum Hamming distance are found both analytically and algorithmically. The bounds indicate that the minimum distance grows with block length. Near-codewords are one of the causes for error floors in LDPC codes; the new construction provides a good framework for studying near-codewords in LDPC codes. Nine example codes are given, and computer simulation results show the excellent error performance of these codes. Finally, connections are made between this new LDPC construction and turbo codes using interleavers generated by quadratic permutation polynomials.
cs/0506092
Emergent Statistical Wealth Distributions in Simple Monetary Exchange Models: A Critical Review
cs.MA
This paper reviews recent attempts at modelling inequality of wealth as an emergent phenomenon of interacting-agent processes. We point out that recent models of wealth condensation which draw their inspiration from molecular dynamics have, in fact, reinvented a process introduced quite some time ago by Angle (1986) in the sociological literature. We emphasize some problematic aspects of simple wealth exchange models and contrast them with a monetary model based on economic principles of market mediated exchange. The paper also reports new results on the influence of market power on the wealth distribution in statistical equilibrium. As it turns out, inequality increases but market power alone is not sufficient for changing the exponential tails of simple exchange models into Pareto tails.
cs/0506093
On Maximum Contention-Free Interleavers and Permutation Polynomials over Integer Rings
cs.IT math.IT
An interleaver is a critical component for the channel coding performance of turbo codes. Algebraic constructions are of particular interest because they admit analytical designs and simple, practical hardware implementation. Contention-free interleavers have been recently shown to be suitable for parallel decoding of turbo codes. In this correspondence, it is shown that permutation polynomials generate maximum contention-free interleavers, i.e., every factor of the interleaver length becomes a possible degree of parallel processing of the decoder. Further, it is shown by computer simulations that turbo codes using these interleavers perform very well for the 3rd Generation Partnership Project (3GPP) standard.
cs/0506094
Universal Codes as a Basis for Nonparametric Testing of Serial Independence for Time Series
cs.IT math.IT
We consider a stationary and ergodic source $p$ generated symbols $x_1 ... x_t$ from some finite set $A$ and a null hypothesis $H_0$ that $p$ is Markovian source with memory (or connectivity) not larger than $m, (m >= 0).$ The alternative hypothesis $H_1$ is that the sequence is generated by a stationary and ergodic source, which differs from the source under $H_0$. In particular, if $m= 0$ we have the null hypothesis $H_0$ that the sequence is generated by Bernoully source (or the hypothesis that $x_1 ...x_t$ are independent.) Some new tests which are based on universal codes and universal predictors, are suggested.
cs/0506095
Deriving a Stationary Dynamic Bayesian Network from a Logic Program with Recursive Loops
cs.AI cs.LG cs.LO
Recursive loops in a logic program present a challenging problem to the PLP framework. On the one hand, they loop forever so that the PLP backward-chaining inferences would never stop. On the other hand, they generate cyclic influences, which are disallowed in Bayesian networks. Therefore, in existing PLP approaches logic programs with recursive loops are considered to be problematic and thus are excluded. In this paper, we propose an approach that makes use of recursive loops to build a stationary dynamic Bayesian network. Our work stems from an observation that recursive loops in a logic program imply a time sequence and thus can be used to model a stationary dynamic Bayesian network without using explicit time parameters. We introduce a Bayesian knowledge base with logic clauses of the form $A \leftarrow A_1,...,A_l, true, Context, Types$, which naturally represents the knowledge that the $A_i$s have direct influences on $A$ in the context $Context$ under the type constraints $Types$. We then use the well-founded model of a logic program to define the direct influence relation and apply SLG-resolution to compute the space of random variables together with their parental connections. We introduce a novel notion of influence clauses, based on which a declarative semantics for a Bayesian knowledge base is established and algorithms for building a two-slice dynamic Bayesian network from a logic program are developed.
cs/0506101
Efficient Multiclass Implementations of L1-Regularized Maximum Entropy
cs.LG cs.CL
This paper discusses the application of L1-regularized maximum entropy modeling or SL1-Max [9] to multiclass categorization problems. A new modification to the SL1-Max fast sequential learning algorithm is proposed to handle conditional distributions. Furthermore, unlike most previous studies, the present research goes beyond a single type of conditional distribution. It describes and compares a variety of modeling assumptions about the class distribution (independent or exclusive) and various types of joint or conditional distributions. It results in a new methodology for combining binary regularized classifiers to achieve multiclass categorization. In this context, Maximum Entropy can be considered as a generic and efficient regularized classification tool that matches or outperforms the state-of-the art represented by AdaBoost and SVMs.
cs/0506102
On $m$-dimensional toric codes
cs.IT math.AC math.AG math.IT
Toric codes are a class of $m$-dimensional cyclic codes introduced recently by J. Hansen. They may be defined as evaluation codes obtained from monomials corresponding to integer lattice points in an integral convex polytope $P \subseteq \R^m$. As such, they are in a sense a natural extension of Reed-Solomon codes. Several authors have used intersection theory on toric surfaces to derive bounds on the minimum distance of some toric codes with $m = 2$. In this paper, we will provide a more elementary approach that applies equally well to many toric codes for all $m \ge 2$. Our methods are based on a sort of multivariate generalization of Vandermonde determinants that has also been used in the study of multivariate polynomial interpolation. We use these Vandermonde determinants to determine the minimum distance of toric codes from rectangular polytopes and simplices. We also prove a general result showing that if there is a unimodular integer affine transformation taking one polytope $P_1$ to a second polytope $P_2$, then the corresponding toric codes are monomially equivalent (hence have the same parameters). We use this to begin a classification of two-dimensional toric codes with small dimension.
cs/0507001
Asymptotically Optimal Tree-based Group Key Management Schemes
cs.IT cs.CR math.IT
In key management schemes that realize secure multicast communications encrypted by group keys on a public network, tree structures are often used to update the group keys efficiently. Selcuk and Sidhu have proposed an efficient scheme which updates dynamically the tree structures based on the withdrawal probabilities of members. In this paper, it is shown that Selcuk-Sidhu scheme is asymptotically optimal for the cost of withdrawal. Furthermore, a new key management scheme, which takes account of key update costs of joining in addition to withdrawal, is proposed. It is proved that the proposed scheme is also asymptotically optimal, and it is shown by simulation that it can attain good performance for nonasymptotic cases.
cs/0507002
The Three Node Wireless Network: Achievable Rates and Cooperation Strategies
cs.IT math.IT
We consider a wireless network composed of three nodes and limited by the half-duplex and total power constraints. This formulation encompasses many of the special cases studied in the literature and allows for capturing the common features shared by them. Here, we focus on three special cases, namely 1) Relay Channel, 2) Multicast Channel, and 3) Conference Channel. These special cases are judicially chosen to reflect varying degrees of complexity while highlighting the common ground shared by the different variants of the three node wireless network. For the relay channel, we propose a new cooperation scheme that exploits the wireless feedback gain. This scheme combines the benefits of decode-and-forward and compress-and-forward strategies and avoids the idealistic feedback assumption adopted in earlier works. Our analysis of the achievable rate of this scheme reveals the diminishing feedback gain at both the low and high signal-to-noise ratio regimes. Inspired by the proposed feedback strategy, we identify a greedy cooperation framework applicable to both the multicast and conference channels. Our performance analysis reveals several nice properties of the proposed greedy approach and the central role of cooperative source-channel coding in exploiting the receiver side information in the wireless network setting. Our proofs for the cooperative multicast with side-information rely on novel nested and independent binning encoders along with a list decoder.
cs/0507004
An End-to-End Probabilistic Network Calculus with Moment Generating Functions
cs.IT cs.PF math.IT
Network calculus is a min-plus system theory for performance evaluation of queuing networks. Its elegance stems from intuitive convolution formulas for concatenation of deterministic servers. Recent research dispenses with the worst-case assumptions of network calculus to develop a probabilistic equivalent that benefits from statistical multiplexing. Significant achievements have been made, owing for example to the theory of effective bandwidths, however, the outstanding scalability set up by concatenation of deterministic servers has not been shown. This paper establishes a concise, probabilistic network calculus with moment generating functions. The presented work features closed-form, end-to-end, probabilistic performance bounds that achieve the objective of scaling linearly in the number of servers in series. The consistent application of moment generating functions put forth in this paper utilizes independence beyond the scope of current statistical multiplexing of flows. A relevant additional gain is demonstrated for tandem servers with independent cross-traffic.
cs/0507005
A Genetic Algorithm Based Finger Selection Scheme for UWB MMSE Rake Receivers
cs.IT math.IT
Due to a large number of multipath components in a typical ultra wideband (UWB) system, selective Rake (SRake) receivers, which combine energy from a subset of multipath components, are commonly employed. In order to optimize system performance, an optimal selection of multipath components to be employed at fingers of an SRake receiver needs to be considered. In this paper, this finger selection problem is investigated for a minimum mean square error (MMSE) UWB SRake receiver. Since the optimal solution is NP hard, a genetic algorithm (GA) based iterative scheme is proposed, which can achieve near-optimal performance after a reasonable number of iterations. Simulation results are presented to compare the performance of the proposed finger selection algorithm with those of the conventional and optimal schemes.
cs/0507006
A Two-Step Time of Arrival Estimation Algorithm for Impulse Radio Ultra Wideband Systems
cs.IT math.IT
High time resolution of ultra wideband (UWB) signals facilitates very precise positioning capabilities based on time-of-arrival (TOA) measurements. Although the theoretical lower bound for TOA estimation can be achieved by the maximum likelihood principle, it is impractical due to the need for extremely high-rate sampling and the presence of large number of multipath components. On the other hand, the conventional correlation-based algorithm, which serially searches possible signal delays, takes a very long time to estimate the TOA of a received UWB signal. Moreover, the first signal path does not always have the strongest correlation output. Therefore, first path detection algorithms need to be considered. In this paper, a data-aided two-step TOA estimation algorithm is proposed. In order to speed up the estimation process, the first step estimates the rough TOA of the received signal based on received signal energy. Then, in the second step, the arrival time of the first signal path is estimated by considering a hypothesis testing approach. The proposed scheme uses low-rate correlation outputs, and is able to perform accurate TOA estimation in reasonable time intervals. The simulation results are presented to analyze the performance of the estimator.
cs/0507010
A Study for the Feature Core of Dynamic Reduct
cs.AI
To the reduct problems of decision system, the paper proposes the notion of dynamic core according to the dynamic reduct model. It describes various formal definitions of dynamic core, and discusses some properties about dynamic core. All of these show that dynamic core possesses the essential characters of the feature core.
cs/0507011
A Utility-Based Approach to Power Control and Receiver Design in Wireless Data Networks
cs.IT math.IT
In this work, the cross-layer design problem of joint multiuser detection and power control is studied using a game-theoretic approach. The uplink of a direct-sequence code division multiple access (DS-CDMA) data network is considered and a non-cooperative game is proposed in which users in the network are allowed to choose their uplink receivers as well as their transmit powers to maximize their own utilities. The utility function measures the number of reliable bits transmitted by the user per joule of energy consumed. Focusing on linear receivers, the Nash equilibrium for the proposed game is derived. It is shown that the equilibrium is one where the powers are SIR-balanced with the minimum mean square error (MMSE) detector as the receiver. In addition, this framework is used to study power control games for the matched filter, the decorrelator, and the MMSE detector; and the receivers' performance is compared in terms of the utilities achieved at equilibrium (in bits/Joule). The optimal cooperative solution is also discussed and compared with the non-cooperative approach. Extensions of the results to the case of multiple receive antennas are also presented. In addition, an admission control scheme based on maximizing the total utility in the network is proposed.
cs/0507015
Duality between Packings and Coverings of the Hamming Space
cs.IT cs.DM math.IT
We investigate the packing and covering densities of linear and nonlinear binary codes, and establish a number of duality relationships between the packing and covering problems. Specifically, we prove that if almost all codes (in the class of linear or nonlinear codes) are good packings, then only a vanishing fraction of codes are good coverings, and vice versa: if almost all codes are good coverings, then at most a vanishing fraction of codes are good packings. We also show that any specific maximal binary code is either a good packing or a good covering, in a certain well-defined sense.
cs/0507018
Optimal and Suboptimal Detection of Gaussian Signals in Noise: Asymptotic Relative Efficiency
cs.IT math.IT
The performance of Bayesian detection of Gaussian signals using noisy observations is investigated via the error exponent for the average error probability. Under unknown signal correlation structure or limited processing capability it is reasonable to use the simple quadratic detector that is optimal in the case of an independent and identically distributed (i.i.d.) signal. Using the large deviations principle, the performance of this detector (which is suboptimal for non-i.i.d. signals) is compared with that of the optimal detector for correlated signals via the asymptotic relative efficiency defined as the ratio between sample sizes of two detectors required for the same performance in the large-sample-size regime. The effects of SNR on the ARE are investigated. It is shown that the asymptotic efficiency of the simple quadratic detector relative to the optimal detector converges to one as the SNR increases without bound for any bounded spectrum, and that the simple quadratic detector performs as well as the optimal detector for a wide range of the correlation values at high SNR.
cs/0507022
On Hilberg's Law and Its Links with Guiraud's Law
cs.CL cs.IT math.IT
Hilberg (1990) supposed that finite-order excess entropy of a random human text is proportional to the square root of the text length. Assuming that Hilberg's hypothesis is true, we derive Guiraud's law, which states that the number of word types in a text is greater than proportional to the square root of the text length. Our derivation is based on some mathematical conjecture in coding theory and on several experiments suggesting that words can be defined approximately as the nonterminals of the shortest context-free grammar for the text. Such operational definition of words can be applied even to texts deprived of spaces, which do not allow for Mandelbrot's ``intermittent silence'' explanation of Zipf's and Guiraud's laws. In contrast to Mandelbrot's, our model assumes some probabilistic long-memory effects in human narration and might be capable of explaining Menzerath's law.
cs/0507023
Two-dimensional cellular automata and the analysis of correlated time series
cs.AI
Correlated time series are time series that, by virtue of the underlying process to which they refer, are expected to influence each other strongly. We introduce a novel approach to handle such time series, one that models their interaction as a two-dimensional cellular automaton and therefore allows them to be treated as a single entity. We apply our approach to the problems of filling gaps and predicting values in rainfall time series. Computational results show that the new approach compares favorably to Kalman smoothing and filtering.
cs/0507024
Experiments in Clustering Homogeneous XML Documents to Validate an Existing Typology
cs.IR
This paper presents some experiments in clustering homogeneous XMLdocuments to validate an existing classification or more generally anorganisational structure. Our approach integrates techniques for extracting knowledge from documents with unsupervised classification (clustering) of documents. We focus on the feature selection used for representing documents and its impact on the emerging classification. We mix the selection of structured features with fine textual selection based on syntactic characteristics.We illustrate and evaluate this approach with a collection of Inria activity reports for the year 2003. The objective is to cluster projects into larger groups (Themes), based on the keywords or different chapters of these activity reports. We then compare the results of clustering using different feature selections, with the official theme structure used by Inria.
cs/0507025
Comparison of Resampling Schemes for Particle Filtering
cs.CE
This contribution is devoted to the comparison of various resampling approaches that have been proposed in the literature on particle filtering. It is first shown using simple arguments that the so-called residual and stratified methods do yield an improvement over the basic multinomial resampling approach. A simple counter-example showing that this property does not hold true for systematic resampling is given. Finally, some results on the large-sample behavior of the simple bootstrap filter algorithm are given. In particular, a central limit theorem is established for the case where resampling is performed using the residual approach.
cs/0507026
Hard Problems of Algebraic Geometry Codes
cs.IT math.IT
The minimum distance is one of the most important combinatorial characterizations of a code. The maximum likelihood decoding problem is one of the most important algorithmic problems of a code. While these problems are known to be hard for general linear codes, the techniques used to prove their hardness often rely on the construction of artificial codes. In general, much less is known about the hardness of the specific classes of natural linear codes. In this paper, we show that both problems are NP-hard for algebraic geometry codes. We achieve this by reducing a well-known NP-complete problem to these problems using a randomized algorithm. The family of codes in the reductions are based on elliptic curves. They have positive rates, but the alphabet sizes are exponential in the block lengths.
cs/0507027
Anyone but Him: The Complexity of Precluding an Alternative
cs.GT cs.CC cs.MA
Preference aggregation in a multiagent setting is a central issue in both human and computer contexts. In this paper, we study in terms of complexity the vulnerability of preference aggregation to destructive control. That is, we study the ability of an election's chair to, through such mechanisms as voter/candidate addition/suppression/partition, ensure that a particular candidate (equivalently, alternative) does not win. And we study the extent to which election systems can make it impossible, or computationally costly (NP-complete), for the chair to execute such control. Among the systems we study--plurality, Condorcet, and approval voting--we find cases where systems immune or computationally resistant to a chair choosing the winner nonetheless are vulnerable to the chair blocking a victory. Beyond that, we see that among our studied systems no one system offers the best protection against destructive control. Rather, the choice of a preference aggregation system will depend closely on which types of control one wishes to be protected against. We also find concrete cases where the complexity of or susceptibility to control varies dramatically based on the choice among natural tie-handling rules.
cs/0507029
ATNoSFERES revisited
cs.AI
ATNoSFERES is a Pittsburgh style Learning Classifier System (LCS) in which the rules are represented as edges of an Augmented Transition Network. Genotypes are strings of tokens of a stack-based language, whose execution builds the labeled graph. The original ATNoSFERES, using a bitstring to represent the language tokens, has been favorably compared in previous work to several Michigan style LCSs architectures in the context of Non Markov problems. Several modifications of ATNoSFERES are proposed here: the most important one conceptually being a representational change: each token is now represented by an integer, hence the genotype is a string of integers; several other modifications of the underlying grammar language are also proposed. The resulting ATNoSFERES-II is validated on several standard animat Non Markov problems, on which it outperforms all previously published results in the LCS literature. The reasons for these improvement are carefully analyzed, and some assumptions are proposed on the underlying mechanisms in order to explain these good results.
cs/0507031
The error-floor of LDPC codes in the Laplacian channel
cs.IT cond-mat.dis-nn math.IT
We analyze the performance of Low-Density-Parity-Check codes in the error-floor domain where the Signal-to-Noise-Ratio, s, is large, s >> 1. We describe how the instanton method of theoretical physics, recently adapted to coding theory, solves the problem of characterizing the error-floor domain in the Laplacian channel. An example of the (155,64,20) LDPC code with four iterations (each iteration consisting of two semi-steps: from bits-to-checks and from checks-to-bits) of the min-sum decoding is discussed. A generalized computational tree analysis is devised to explain the rational structure of the leading instantons. The asymptotic for the symbol Bit-Error-Rate in the error-floor domain is comprised of individual instanton contributions, each estimated as ~ \exp(-l_{inst;L} s), where the effective distances, l_{inst;L}, of the the leading instantons are 7.6, 8.0 and 8.0 respectively. (The Hamming distance of the code is 20.) The analysis shows that the instantons are distinctly different from the ones found for the same coding/decoding scheme performing over the Gaussian channel. We validate instanton results against direct simulations and offer an explanation for remarkable performance of the instanton approximation not only in the extremal, s -> \infty, limit but also at the moderate s values of practical interest.
cs/0507032
Introduction to Quantum Message Space
cs.IT math.IT math.OA quant-ph
This paper develops the quantum analog of the message ensemble of classical information theory as developed by Shannon and Khinchin. The principal mathematical tool is harmonic analysis on the free group with two generators.
cs/0507033
Multiresolution Kernels
cs.LG
We present in this work a new methodology to design kernels on data which is structured with smaller components, such as text, images or sequences. This methodology is a template procedure which can be applied on most kernels on measures and takes advantage of a more detailed "bag of components" representation of the objects. To obtain such a detailed description, we consider possible decompositions of the original bag into a collection of nested bags, following a prior knowledge on the objects' structure. We then consider these smaller bags to compare two objects both in a detailed perspective, stressing local matches between the smaller bags, and in a global or coarse perspective, by considering the entire bag. This multiresolution approach is likely to be best suited for tasks where the coarse approach is not precise enough, and where a more subtle mixture of both local and global similarities is necessary to compare objects. The approach presented here would not be computationally tractable without a factorization trick that we introduce before presenting promising results on an image retrieval task.
cs/0507035
Enhancing Global SLS-Resolution with Loop Cutting and Tabling Mechanisms
cs.LO cs.AI
Global SLS-resolution is a well-known procedural semantics for top-down computation of queries under the well-founded model. It inherits from SLDNF-resolution the {\em linearity} property of derivations, which makes it easy and efficient to implement using a simple stack-based memory structure. However, like SLDNF-resolution it suffers from the problem of infinite loops and redundant computations. To resolve this problem, in this paper we develop a new procedural semantics, called {\em SLTNF-resolution}, by enhancing Global SLS-resolution with loop cutting and tabling mechanisms. SLTNF-resolution is sound and complete w.r.t. the well-founded semantics for logic programs with the bounded-term-size property, and is superior to existing linear tabling procedural semantics such as SLT-resolution.
cs/0507039
Distributed Regression in Sensor Networks: Training Distributively with Alternating Projections
cs.LG cs.AI cs.CV cs.DC cs.IT math.IT
Wireless sensor networks (WSNs) have attracted considerable attention in recent years and motivate a host of new challenges for distributed signal processing. The problem of distributed or decentralized estimation has often been considered in the context of parametric models. However, the success of parametric methods is limited by the appropriateness of the strong statistical assumptions made by the models. In this paper, a more flexible nonparametric model for distributed regression is considered that is applicable in a variety of WSN applications including field estimation. Here, starting with the standard regularized kernel least-squares estimator, a message-passing algorithm for distributed estimation in WSNs is derived. The algorithm can be viewed as an instantiation of the successive orthogonal projection (SOP) algorithm. Various practical aspects of the algorithm are discussed and several numerical simulations validate the potential of the approach.
cs/0507040
Pattern Recognition for Conditionally Independent Data
cs.LG cs.AI cs.CV
In this work we consider the task of relaxing the i.i.d assumption in pattern recognition (or classification), aiming to make existing learning algorithms applicable to a wider range of tasks. Pattern recognition is guessing a discrete label of some object based on a set of given examples (pairs of objects and labels). We consider the case of deterministically defined labels. Traditionally, this task is studied under the assumption that examples are independent and identically distributed. However, it turns out that many results of pattern recognition theory carry over a weaker assumption. Namely, under the assumption of conditional independence and identical distribution of objects, while the only assumption on the distribution of labels is that the rate of occurrence of each label should be above some positive threshold. We find a broad class of learning algorithms for which estimations of the probability of a classification error achieved under the classical i.i.d. assumption can be generalised to the similar estimates for the case of conditionally i.i.d. examples.
cs/0507041
Monotone Conditional Complexity Bounds on Future Prediction Errors
cs.LG cs.AI cs.IT math.IT
We bound the future loss when predicting any (computably) stochastic sequence online. Solomonoff finitely bounded the total deviation of his universal predictor M from the true distribution m by the algorithmic complexity of m. Here we assume we are at a time t>1 and already observed x=x_1...x_t. We bound the future prediction performance on x_{t+1}x_{t+2}... by a new variant of algorithmic complexity of m given x, plus the complexity of the randomness deficiency of x. The new complexity is monotone in its condition in the sense that this complexity can only decrease if the condition is prolonged. We also briefly discuss potential generalizations to Bayesian model classes and to classification problems.
cs/0507042
The MammoGrid Virtual Organisation - Federating Distributed Mammograms
cs.DC cs.DB
The MammoGrid project aims to deliver a prototype which enables the effective collaboration between radiologists using grid, service-orientation and database solutions. The grid technologies and service-based database management solution provide the platform for integrating diverse and distributed resources, creating what is called a virtual organisation. The MammoGrid Virtual Organisation facilitates the sharing and coordinated access to mammography data, medical imaging software and computing resources of participating hospitals. Hospitals manage their local database of mammograms, but in addition, radiologists who are part of this organisation can share mammograms, reports, results and image analysis software. The MammoGrid Virtual Organisation is a federation of autonomous multi-centres sites which transcends national boundaries. This paper outlines the service-based approach in the creation and management of the federated distributed mammography database and discusses the role of virtual organisations in distributed image analysis.
cs/0507044
Defensive Universal Learning with Experts
cs.LG
This paper shows how universal learning can be achieved with expert advice. To this aim, we specify an experts algorithm with the following characteristics: (a) it uses only feedback from the actions actually chosen (bandit setup), (b) it can be applied with countably infinite expert classes, and (c) it copes with losses that may grow in time appropriately slowly. We prove loss bounds against an adaptive adversary. From this, we obtain a master algorithm for "reactive" experts problems, which means that the master's actions may influence the behavior of the adversary. Our algorithm can significantly outperform standard experts algorithms on such problems. Finally, we combine it with a universal expert class. The resulting universal learner performs -- in a certain sense -- almost as well as any computable strategy, for any online decision problem. We also specify the (worst-case) convergence speed, which is very slow.
cs/0507045
In the beginning was game semantics
cs.LO cs.AI math.LO
This article presents an overview of computability logic -- the game-semantically constructed logic of interactive computational tasks and resources. There is only one non-overview, technical section in it, devoted to a proof of the soundness of affine logic with respect to the semantics of computability logic. A comprehensive online source on the subject can be found at http://www.cis.upenn.edu/~giorgi/cl.html
cs/0507048
Redundancy in Logic III: Non-Mononotonic Reasoning
cs.LO cs.AI cs.CC
Results about the redundancy of circumscriptive and default theories are presented. In particular, the complexity of establishing whether a given theory is redundant is establihsed.
cs/0507053
Nonrepetitive Paths and Cycles in Graphs with Application to Sudoku
cs.DS cs.AI
We provide a simple linear time transformation from a directed or undirected graph with labeled edges to an unlabeled digraph, such that paths in the input graph in which no two consecutive edges have the same label correspond to paths in the transformed graph and vice versa. Using this transformation, we provide efficient algorithms for finding paths and cycles with no two consecutive equal labels. We also consider related problems where the paths and cycles are required to be simple; we find efficient algorithms for the undirected case of these problems but show the directed case to be NP-complete. We apply our path and cycle finding algorithms in a program for generating and solving Sudoku puzzles, and show experimentally that they lead to effective puzzle-solving rules that may also be of interest to human Sudoku puzzle solvers.
cs/0507055
ReacProc: A Tool to Process Reactions Describing Particle Interactions
cs.CE
ReacProc is a program written in C/C++ programming language which can be used (1) to check out of reactions describing particles interactions against conservation laws and (2) to reduce input reaction into some canonical form. A table with particles properties is available within ReacProc package.
cs/0507056
Explorations in engagement for humans and robots
cs.AI cs.CL cs.RO
This paper explores the concept of engagement, the process by which individuals in an interaction start, maintain and end their perceived connection to one another. The paper reports on one aspect of engagement among human interactors--the effect of tracking faces during an interaction. It also describes the architecture of a robot that can participate in conversational, collaborative interactions with engagement gestures. Finally, the paper reports on findings of experiments with human participants who interacted with a robot when it either performed or did not perform engagement gestures. Results of the human-robot studies indicate that people become engaged with robots: they direct their attention to the robot more often in interactions where engagement gestures are present, and they find interactions more appropriate when engagement gestures are present than when they are not.
cs/0507058
Paving the Way for Image Understanding: A New Kind of Image Decomposition is Desired
cs.CV
In this paper we present an unconventional image segmentation approach which is devised to meet the requirements of image understanding and pattern recognition tasks. Generally image understanding assumes interplay of two sub-processes: image information content discovery and image information content interpretation. Despite of its widespread use, the notion of "image information content" is still ill defined, intuitive, and ambiguous. Most often, it is used in the Shannon's sense, which means information content assessment averaged over the whole signal ensemble. Humans, however,rarely resort to such estimates. They are very effective in decomposing images into their meaningful constituents and focusing attention to the perceptually relevant image parts. We posit that following the latest findings in human attention vision studies and the concepts of Kolmogorov's complexity theory an unorthodox segmentation approach can be proposed that provides effective image decomposition to information preserving image fragments well suited for subsequent image interpretation. We provide some illustrative examples, demonstrating effectiveness of this approach.
cs/0507059
Data complexity of answering conjunctive queries over SHIQ knowledge bases
cs.LO cs.AI cs.CC
An algorithm for answering conjunctive queries over SHIQ knowledge bases that is coNP in data complexity is given. The algorithm is based on the tableau algorithm for reasoning with individuals in SHIQ. The blocking conditions of the tableau are weakened in such a way that the set of models the modified algorithm yields suffices to check query entailment. The modified blocking conditions are based on the ones proposed by Levy and Rousset for reasoning with Horn Rules in the description logic ALCNR.
cs/0507060
The Entropy of a Binary Hidden Markov Process
cs.IT cond-mat.stat-mech math.IT math.ST stat.TH
The entropy of a binary symmetric Hidden Markov Process is calculated as an expansion in the noise parameter epsilon. We map the problem onto a one-dimensional Ising model in a large field of random signs and calculate the expansion coefficients up to second order in epsilon. Using a conjecture we extend the calculation to 11th order and discuss the convergence of the resulting series.
cs/0507062
FPL Analysis for Adaptive Bandits
cs.LG
A main problem of "Follow the Perturbed Leader" strategies for online decision problems is that regret bounds are typically proven against oblivious adversary. In partial observation cases, it was not clear how to obtain performance guarantees against adaptive adversary, without worsening the bounds. We propose a conceptually simple argument to resolve this problem. Using this, a regret bound of O(t^(2/3)) for FPL in the adversarial multi-armed bandit problem is shown. This bound holds for the common FPL variant using only the observations from designated exploration rounds. Using all observations allows for the stronger bound of O(t^(1/2)), matching the best bound known so far (and essentially the known lower bound) for adversarial bandits. Surprisingly, this variant does not even need explicit exploration, it is self-stabilizing. However the sampling probabilities have to be either externally provided or approximated to sufficient accuracy, using O(t^2 log t) samples in each step.
cs/0507065
A Fast Greedy Algorithm for Outlier Mining
cs.DB cs.AI
The task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. In [38], the problem of outlier detection in categorical data is defined as an optimization problem and a local-search heuristic based algorithm (LSA) is presented. However, as is the case with most iterative type algorithms, the LSA algorithm is still very time-consuming on very large datasets. In this paper, we present a very fast greedy algorithm for mining outliers under the same optimization model. Experimental results on real datasets and large synthetic datasets show that: (1) Our algorithm has comparable performance with respect to those state-of-art outlier detection algorithms on identifying true outliers and (2) Our algorithm can be an order of magnitude faster than LSA algorithm.
cs/0507067
Conjunctive Query Containment and Answering under Description Logics Constraints
cs.DB cs.AI
Query containment and query answering are two important computational tasks in databases. While query answering amounts to compute the result of a query over a database, query containment is the problem of checking whether for every database, the result of one query is a subset of the result of another query. In this paper, we deal with unions of conjunctive queries, and we address query containment and query answering under Description Logic constraints. Every such constraint is essentially an inclusion dependencies between concepts and relations, and their expressive power is due to the possibility of using complex expressions, e.g., intersection and difference of relations, special forms of quantification, regular expressions over binary relations, in the specification of the dependencies. These types of constraints capture a great variety of data models, including the relational, the entity-relationship, and the object-oriented model, all extended with various forms of constraints, and also the basic features of the ontology languages used in the context of the Semantic Web. We present the following results on both query containment and query answering. We provide a method for query containment under Description Logic constraints, thus showing that the problem is decidable, and analyze its computational complexity. We prove that query containment is undecidable in the case where we allow inequalities in the right-hand side query, even for very simple constraints and queries. We show that query answering under Description Logic constraints can be reduced to query containment, and illustrate how such a reduction provides upper bound results with respect to both combined and data complexity.
cs/0507068
On parity check collections for iterative erasure decoding that correct all correctable erasure patterns of a given size
cs.IT cs.DM math.IT
Recently there has been interest in the construction of small parity check sets for iterative decoding of the Hamming code with the property that each uncorrectable (or stopping) set of size three is the support of a codeword and hence uncorrectable anyway. Here we reformulate and generalise the problem, and improve on this construction. First we show that a parity check collection that corrects all correctable erasure patterns of size m for the r-th order Hamming code (i.e, the Hamming code with codimension r) provides for all codes of codimension $r$ a corresponding ``generic'' parity check collection with this property. This leads naturally to a necessary and sufficient condition on such generic parity check collections. We use this condition to construct a generic parity check collection for codes of codimension r correcting all correctable erasure patterns of size at most m, for all r and m <= r, thus generalising the known construction for m=3. Then we discussoptimality of our construction and show that it can be improved for m>=3 and r large enough. Finally we discuss some directions for further research.
cs/0507069
Users and Assessors in the Context of INEX: Are Relevance Dimensions Relevant?
cs.IR
The main aspects of XML retrieval are identified by analysing and comparing the following two behaviours: the behaviour of the assessor when judging the relevance of returned document components; and the behaviour of users when interacting with components of XML documents. We argue that the two INEX relevance dimensions, Exhaustivity and Specificity, are not orthogonal dimensions; indeed, an empirical analysis of each dimension reveals that the grades of the two dimensions are correlated to each other. By analysing the level of agreement between the assessor and the users, we aim at identifying the best units of retrieval. The results of our analysis show that the highest level of agreement is on highly relevant and on non-relevant document components, suggesting that only the end points of the INEX 10-point relevance scale are perceived in the same way by both the assessor and the users. We propose a new definition of relevance for XML retrieval and argue that its corresponding relevance scale would be a better choice for INEX.
cs/0507070
Hybrid XML Retrieval: Combining Information Retrieval and a Native XML Database
cs.IR
This paper investigates the impact of three approaches to XML retrieval: using Zettair, a full-text information retrieval system; using eXist, a native XML database; and using a hybrid system that takes full article answers from Zettair and uses eXist to extract elements from those articles. For the content-only topics, we undertake a preliminary analysis of the INEX 2003 relevance assessments in order to identify the types of highly relevant document components. Further analysis identifies two complementary sub-cases of relevance assessments ("General" and "Specific") and two categories of topics ("Broad" and "Narrow"). We develop a novel retrieval module that for a content-only topic utilises the information from the resulting answer list of a native XML database and dynamically determines the preferable units of retrieval, which we call "Coherent Retrieval Elements". The results of our experiments show that -- when each of the three systems is evaluated against different retrieval scenarios (such as different cases of relevance assessments, different topic categories and different choices of evaluation metrics) -- the XML retrieval systems exhibit varying behaviour and the best performance can be reached for different values of the retrieval parameters. In the case of INEX 2003 relevance assessments for the content-only topics, our newly developed hybrid XML retrieval system is substantially more effective than either Zettair or eXist, and yields a robust and a very effective XML retrieval.
cs/0508001
Dimensions of Copeland-Erdos Sequences
cs.CC cs.IT math.IT
The base-$k$ {\em Copeland-Erd\"os sequence} given by an infinite set $A$ of positive integers is the infinite sequence $\CE_k(A)$ formed by concatenating the base-$k$ representations of the elements of $A$ in numerical order. This paper concerns the following four quantities. The {\em finite-state dimension} $\dimfs (\CE_k(A))$, a finite-state version of classical Hausdorff dimension introduced in 2001. The {\em finite-state strong dimension} $\Dimfs(\CE_k(A))$, a finite-state version of classical packing dimension introduced in 2004. This is a dual of $\dimfs(\CE_k(A))$ satisfying $\Dimfs(\CE_k(A))$ $\geq \dimfs(\CE_k(A))$. The {\em zeta-dimension} $\Dimzeta(A)$, a kind of discrete fractal dimension discovered many times over the past few decades. The {\em lower zeta-dimension} $\dimzeta(A)$, a dual of $\Dimzeta(A)$ satisfying $\dimzeta(A)\leq \Dimzeta(A)$. We prove the following. $\dimfs(\CE_k(A))\geq \dimzeta(A)$. This extends the 1946 proof by Copeland and Erd\"os that the sequence $\CE_k(\mathrm{PRIMES})$ is Borel normal. $\Dimfs(\CE_k(A))\geq \Dimzeta(A)$. These bounds are tight in the strong sense that these four quantities can have (simultaneously) any four values in $[0,1]$ satisfying the four above-mentioned inequalities.
cs/0508007
Regularity of Position Sequences
cs.CV cs.AI cs.LG q-bio.NC
A person is given a numbered sequence of positions on a sheet of paper. The person is asked, "Which will be the next (or the next after that) position?" Everyone has an opinion as to how he or she would proceed. There are regular sequences for which there is general agreement on how to continue. However, there are less regular sequences for which this assessment is less certain. There are sequences for which every continuation is perceived to be arbitrary. I would like to present a mathematical model that reflects these opinions and perceptions with the aid of a valuation function. It is necessary to apply a rich set of invariant features of position sequences to ensure the quality of this model. All other properties of the model are arbitrary.
cs/0508008
The accurate optimal-success/error-rate calculations applied to the realizations of the reliable and short-period integer ambiguity resolution in carrier-phase GPS/GNSS positioning
cs.IT math.IT
The maximum-marginal-a-posteriori success rate of statistical decision under multivariate Gaussian error distribution on an integer lattice is almost rigorously calculated by using union-bound approximation and Monte Carlo integration. These calculations are applied to the revelation of the various possible realizations of the reliable and short-period integer ambiguity resolution in precise carrier-phase relative positioning by GPS/GNSS. The theoretical foundation and efficient methodology are systematically developed, and two types of the enhancement of union-bound approximation are proposed and examined. The results revealed include an extremely high reliability under the condition of accurate carrier-phase measurements and a large number of visible satellites, its heavy degradation caused by the slight amount of differentiated ionospheric delays due to the nonvanishing baseline length between rover and reference receivers, and the advantages of the use of the multiple carrier frequencies. The succeeding initialization of the integer ambiguities is shown to overcome the disadvantageous condition of the nonvanishing baseline length effectively due to the reasonably assumed temporal and spatial constancy of differentiated ionospheric delays.
cs/0508012
n-Channel Asymmetric Multiple-Description Lattice Vector Quantization
cs.IT math.IT
We present analytical expressions for optimal entropy-constrained multiple-description lattice vector quantizers which, under high-resolutions assumptions, minimize the expected distortion for given packet-loss probabilities. We consider the asymmetric case where packet-loss probabilities and side entropies are allowed to be unequal and find optimal quantizers for any number of descriptions in any dimension. We show that the normalized second moments of the side-quantizers are given by that of an $L$-dimensional sphere independent of the choice of lattices. Furthermore, we show that the optimal bit-distribution among the descriptions is not unique. In fact, within certain limits, bits can be arbitrarily distributed.
cs/0508013
Relations between the Local Weight Distributions of a Linear Block Code, Its Extended Code, and Its Even Weight Subcode
cs.IT math.IT
Relations between the local weight distributions of a binary linear code, its extended code, and its even weight subcode are presented. In particular, for a code of which the extended code is transitive invariant and contains only codewords with weight multiples of four, the local weight distribution can be obtained from that of the extended code. Using the relations, the local weight distributions of the $(127,k)$ primitive BCH codes for $k\leq50$, the $(127,64)$ punctured third-order Reed-Muller, and their even weight subcodes are obtained from the local weight distribution of the $(128,k)$ extended primitive BCH codes for $k\leq50$ and the $(128,64)$ third-order Reed-Muller code. We also show an approach to improve an algorithm for computing the local weight distribution proposed before.
cs/0508014
The Benefit of Thresholding in LP Decoding of LDPC Codes
cs.IT math.IT
Consider data transmission over a binary-input additive white Gaussian noise channel using a binary low-density parity-check code. We ask the following question: Given a decoder that takes log-likelihood ratios as input, does it help to modify the log-likelihood ratios before decoding? If we use an optimal decoder then it is clear that modifying the log-likelihoods cannot possibly help the decoder's performance, and so the answer is "no." However, for a suboptimal decoder like the linear programming decoder, the answer might be "yes": In this paper we prove that for certain interesting classes of low-density parity-check codes and large enough SNRs, it is advantageous to truncate the log-likelihood ratios before passing them to the linear programming decoder.
cs/0508015
Chosen-ciphertext attack on noncommutative Polly Cracker
cs.IT cs.CR math.IT
We propose a chosen-ciphertext attack on recently presented noncommutative variant of the well-known Polly Cracker cryptosystem. We show that if one chooses parameters for this noncommutative Polly Cracker as initially proposed, than the system should be claimed as insecure.
cs/0508017
Enhancing Content-And-Structure Information Retrieval using a Native XML Database
cs.IR
Three approaches to content-and-structure XML retrieval are analysed in this paper: first by using Zettair, a full-text information retrieval system; second by using eXist, a native XML database, and third by using a hybrid XML retrieval system that uses eXist to produce the final answers from likely relevant articles retrieved by Zettair. INEX 2003 content-and-structure topics can be classified in two categories: the first retrieving full articles as final answers, and the second retrieving more specific elements within articles as final answers. We show that for both topic categories our initial hybrid system improves the retrieval effectiveness of a native XML database. For ranking the final answer elements, we propose and evaluate a novel retrieval model that utilises the structural relationships between the answer elements of a native XML database and retrieves Coherent Retrieval Elements. The final results of our experiments show that when the XML retrieval task focusses on highly relevant elements our hybrid XML retrieval system with the Coherent Retrieval Elements module is 1.8 times more effective than Zettair and 3 times more effective than eXist, and yields an effective content-and-structure XML retrieval.
cs/0508018
Spectral Factorization, Whitening- and Estimation Filter -- Stability, Smoothness Properties and FIR Approximation Behavior
cs.IT math.IT
A Wiener filter can be interpreted as a cascade of a whitening- and an estimation filter. This paper gives a detailed investigates of the properties of these two filters. Then the practical consequences for the overall Wiener filter are ascertained. It is shown that if the given spectral densities are smooth (Hoelder continuous) functions, the resulting Wiener filter will always be stable and can be approximated arbitrarily well by a finite impulse response (FIR) filter. Moreover, the smoothness of the spectral densities characterizes how fast the FIR filter approximates the desired filter characteristic. If on the other hand the spectral densities are continuous but not smooth enough, the resulting Wiener filter may not be stable.
cs/0508019
On the Minimal Pseudo-Codewords of Codes from Finite Geometries
cs.IT cs.DM math.IT
In order to understand the performance of a code under maximum-likelihood (ML) decoding, it is crucial to know the minimal codewords. In the context of linear programming (LP) decoding, it turns out to be necessary to know the minimal pseudo-codewords. This paper studies the minimal codewords and minimal pseudo-codewords of some families of codes derived from projective and Euclidean planes. Although our numerical results are only for codes of very modest length, they suggest that these code families exhibit an interesting property. Namely, all minimal pseudo-codewords that are not multiples of a minimal codeword have an AWGNC pseudo-weight that is strictly larger than the minimum Hamming weight of the code. This observation has positive consequences not only for LP decoding but also for iterative decoding.
cs/0508020
Capacity Gain from Transmitter and Receiver Cooperation
cs.IT math.IT
Capacity gain from transmitter and receiver cooperation are compared in a relay network where the cooperating nodes are close together. When all nodes have equal average transmit power along with full channel state information (CSI), it is proved that transmitter cooperation outperforms receiver cooperation, whereas the opposite is true when power is optimally allocated among the nodes but only receiver phase CSI is available. In addition, when the nodes have equal average power with receiver phase CSI only, cooperation is shown to offer no capacity improvement over a non-cooperative scheme with the same average network power. When the system is under optimal power allocation with full CSI, the decode-and-forward transmitter cooperation rate is close to its cut-set capacity upper bound, and outperforms compress-and-forward receiver cooperation. Moreover, it is shown that full CSI is essential in transmitter cooperation, while optimal power allocation is essential in receiver cooperation.
cs/0508022
Matrix Construction Using Cyclic Shifts of a Column
cs.DM cs.CR cs.IT math.IT
This paper describes the synthesis of matrices with good correlation, from cyclic shifts of pseudonoise columns. Optimum matrices result whenever the shift sequence satisfies the constant difference property. Known shift sequences with the constant (or almost constant) difference property are: Quadratic (Polynomial) and Reciprocal Shift modulo prime, Exponential Shift, Legendre Shift, Zech Logarithm Shift, and the shift sequences of some m-arrays. We use these shift sequences to produce arrays for watermarking of digital images. Matrices can also be unfolded into long sequences by diagonal unfolding (with no deterioration in correlation) or row-by-row unfolding, with some degradation in correlation.
cs/0508023
Software Libraries and Their Reuse: Entropy, Kolmogorov Complexity, and Zipf's Law
cs.SE cs.IT cs.PL math.IT
We analyze software reuse from the perspective of information theory and Kolmogorov complexity, assessing our ability to ``compress'' programs by expressing them in terms of software components reused from libraries. A common theme in the software reuse literature is that if we can only get the right environment in place-- the right tools, the right generalizations, economic incentives, a ``culture of reuse'' -- then reuse of software will soar, with consequent improvements in productivity and software quality. The analysis developed in this paper paints a different picture: the extent to which software reuse can occur is an intrinsic property of a problem domain, and better tools and culture can have only marginal impact on reuse rates if the domain is inherently resistant to reuse. We define an entropy parameter $H \in [0,1]$ of problem domains that measures program diversity, and deduce from this upper bounds on code reuse and the scale of components with which we may work. For ``low entropy'' domains with $H$ near 0, programs are highly similar to one another and the domain is amenable to the Component-Based Software Engineering (CBSE) dream of programming by composing large-scale components. For problem domains with $H$ near 1, programs require substantial quantities of new code, with only a modest proportion of an application comprised of reused, small-scale components. Preliminary empirical results from Unix platforms support some of the predictions of our model.
cs/0508024
New Codes for OFDM with Low PMEPR
cs.IT math.IT
In this paper new codes for orthogonal frequency-division multiplexing (OFDM) with tightly controlled peak-to-mean envelope power ratio (PMEPR) are proposed. We identify a new family of sequences occuring in complementary sets and show that such sequences form subsets of a new generalization of the Reed--Muller codes. Contrarily to previous constructions we present a compact description of such codes, which makes them suitable even for larger block lengths. We also show that some previous constructions just occur as special cases in our construction.
cs/0508025
Signature coding for OR channel with asynchronous access
cs.IT math.IT
Signature coding for multiple access OR channel is considered. We prove that in block asynchronous case the upper bound on the minimum code length asymptotically is the same as in the case of synchronous access.
cs/0508026
Simple Maximum-Likelihood Decoding of Generalized First-order Reed-Muller Codes
cs.IT math.IT
An efficient decoder for the generalized first-order Reed-Muller code RM_q(1,m) is essential for the decoding of various block-coding schemes for orthogonal frequency-division multiplexing with reduced peak-to-mean power ratio. We present an efficient and simple maximum-likelihood decoding algorithm for RM_q(1,m). It is shown that this algorithm has lower complexity than other previously known maximum-likelihood decoders for RM_q(1,m).
cs/0508027
Expectation maximization as message passing
cs.IT cs.LG math.IT
Based on prior work by Eckford, it is shown how expectation maximization (EM) may be viewed, and used, as a message passing algorithm in factor graphs.
cs/0508028
Truth-telling Reservations
cs.GT cond-mat.stat-mech cs.MA
We present a mechanism for reservations of bursty resources that is both truthful and robust. It consists of option contracts whose pricing structure induces users to reveal the true likelihoods that they will purchase a given resource. Users are also allowed to adjust their options as their likelihood changes. This scheme helps users save cost and the providers to plan ahead so as to reduce the risk of under-utilization and overbooking. The mechanism extracts revenue similar to that of a monopoly provider practicing temporal pricing discrimination with a user population whose preference distribution is known in advance.
cs/0508029
Selfish vs. Unselfish Optimization of Network Creation
cs.NI cs.AR cs.MA
We investigate several variants of a network creation model: a group of agents builds up a network between them while trying to keep the costs of this network small. The cost function consists of two addends, namely (i) a constant amount for each edge an agent buys and (ii) the minimum number of hops it takes sending messages to other agents. Despite the simplicity of this model, various complex network structures emerge depending on the weight between the two addends of the cost function and on the selfish or unselfish behaviour of the agents.
cs/0508030
Terminated LDPC Convolutional Codes with Thresholds Close to Capacity
cs.IT math.IT
An ensemble of LDPC convolutional codes with parity-check matrices composed of permutation matrices is considered. The convergence of the iterative belief propagation based decoder for terminated convolutional codes in the ensemble is analyzed for binary-input output-symmetric memoryless channels using density evolution techniques. We observe that the structured irregularity in the Tanner graph of the codes leads to significantly better thresholds when compared to corresponding LDPC block codes.
cs/0508031
Capacity Theorems for Quantum Multiple Access Channels
cs.IT math.IT quant-ph
We consider quantum channels with two senders and one receiver. For an arbitrary such channel, we give multi-letter characterizations of two different two-dimensional capacity regions. The first region characterizes the rates at which it is possible for one sender to send classical information while the other sends quantum information. The second region gives the rates at which each sender can send quantum information. We give an example of a channel for which each region has a single-letter description, concluding with a characterization of the rates at which each user can simultaneously send classical and quantum information.
cs/0508032
Polymorphic Self-* Agents for Stigmergic Fault Mitigation in Large-Scale Real-Time Embedded Systems
cs.AI cs.MA
Organization and coordination of agents within large-scale, complex, distributed environments is one of the primary challenges in the field of multi-agent systems. A lot of interest has surfaced recently around self-* (self-organizing, self-managing, self-optimizing, self-protecting) agents. This paper presents polymorphic self-* agents that evolve a core set of roles and behavior based on environmental cues. The agents adapt these roles based on the changing demands of the environment, and are directly implementable in computer systems applications. The design combines strategies from game theory, stigmergy, and other biologically inspired models to address fault mitigation in large-scale, real-time, distributed systems. The agents are embedded within the individual digital signal processors of BTeV, a High Energy Physics experiment consisting of 2500 such processors. Results obtained using a SWARM simulation of the BTeV environment demonstrate the polymorphic character of the agents, and show how this design exceeds performance and reliability metrics obtained from comparable centralized, and even traditional decentralized approaches.
cs/0508034
Channel combining and splitting for cutoff rate improvement
cs.IT math.IT
The cutoff rate $R_0(W)$ of a discrete memoryless channel (DMC) $W$ is often used as a figure of merit, alongside the channel capacity $C(W)$. Given a channel $W$ consisting of two possibly correlated subchannels $W_1$, $W_2$, the capacity function always satisfies $C(W_1)+C(W_2) \le C(W)$, while there are examples for which $R_0(W_1)+R_0(W_2) > R_0(W)$. This fact that cutoff rate can be ``created'' by channel splitting was noticed by Massey in his study of an optical modulation system modeled as a $M$'ary erasure channel. This paper demonstrates that similar gains in cutoff rate can be achieved for general DMC's by methods of channel combining and splitting. Relation of the proposed method to Pinsker's early work on cutoff rate improvement and to Imai-Hirakawa multi-level coding are also discussed.
cs/0508035
Codes for error detection, good or not good
cs.IT math.IT
Linear codes for error detection on a q-ary symmetric channel are studied. It is shown that for given dimension k and minimum distance d, there exists a value \mu(d,k) such that if C is a code of length n >= \mu(d,k), then neither C nor its dual are good for error detection. For d >> k or k << d good approximations for \mu(d,k) are given. A generalization to non-linear codes is also given.
cs/0508036
Exp\'{e}riences de classification d'une collection de documents XML de structure homog\`{e}ne
cs.IR
This paper presents some experiments in clustering homogeneous XMLdocuments to validate an existing classification or more generally anorganisational structure. Our approach integrates techniques for extracting knowledge from documents with unsupervised classification (clustering) of documents. We focus on the feature selection used for representing documents and its impact on the emerging classification. We mix the selection of structured features with fine textual selection based on syntactic characteristics.We illustrate and evaluate this approach with a collection of Inria activity reports for the year 2003. The objective is to cluster projects into larger groups (Themes), based on the keywords or different chapters of these activity reports. We then compare the results of clustering using different feature selections, with the official theme structure used by Inria.
cs/0508039
Tight Bounds on the Redundancy of Huffman Codes
cs.IT math.IT
In this paper we study the redundancy of Huffman codes. In particular, we consider sources for which the probability of one of the source symbols is known. We prove a conjecture of Ye and Yeung regarding the upper bound on the redundancy of such Huffman codes, which yields in a tight upper bound. We also derive a tight lower bound for the redundancy under the same assumption. We further apply the method introduced in this paper to other related problems. It is shown that several other previously known bounds with different constraints follow immediately from our results.
cs/0508040
Bounds on the Capacity of the Blockwise Noncoherent APSK-AWGN Channels
cs.IT math.IT
Capacity of M-ary Amplitude and Phase-Shift Keying(M-APSK) over an Additive White Gaussian Noise(AWGN) channel that also introduces an unknown carrier phase rotation is considered. The phase remains constant over a block of L symbols and it is independent from block to block. Aiming to design codes with equally probable symbols, uniformly distributed channel inputs are assumed. Based on results of Peleg and Shamai for M-ary Phase Shift Keying(M-PSK) modulation, easily computable upper and lower bounds on the effective M-APSK capacity are derived. For moderate M and L and a broad range of Signal-to-Noise Ratios(SNR's), the bounds come close together. As in the case of M-PSK modulation, for large L the coherent capacity is approached.
cs/0508043
Sequential Predictions based on Algorithmic Complexity
cs.IT cs.LG math.IT
This paper studies sequence prediction based on the monotone Kolmogorov complexity Km=-log m, i.e. based on universal deterministic/one-part MDL. m is extremely close to Solomonoff's universal prior M, the latter being an excellent predictor in deterministic as well as probabilistic environments, where performance is measured in terms of convergence of posteriors or losses. Despite this closeness to M, it is difficult to assess the prediction quality of m, since little is known about the closeness of their posteriors, which are the important quantities for prediction. We show that for deterministic computable environments, the "posterior" and losses of m converge, but rapid convergence could only be shown on-sequence; the off-sequence convergence can be slow. In probabilistic environments, neither the posterior nor the losses converge, in general.
cs/0508046
Relaxation Bounds on the Minimum Pseudo-Weight of Linear Block Codes
cs.IT math.IT
Just as the Hamming weight spectrum of a linear block code sheds light on the performance of a maximum likelihood decoder, the pseudo-weight spectrum provides insight into the performance of a linear programming decoder. Using properties of polyhedral cones, we find the pseudo-weight spectrum of some short codes. We also present two general lower bounds on the minimum pseudo-weight. The first bound is based on the column weight of the parity-check matrix. The second bound is computed by solving an optimization problem. In some cases, this bound is more tractable to compute than previously known bounds and thus can be applied to longer codes.
cs/0508047
Further Results on Coding for Reliable Communication over Packet Networks
cs.IT cs.NI math.IT
In "On Coding for Reliable Communication over Packet Networks" (Lun, Medard, and Effros, Proc. 42nd Annu. Allerton Conf. Communication, Control, and Computing, 2004), a capacity-achieving coding scheme for unicast or multicast over lossy wireline or wireless packet networks is presented. We extend that paper's results in two ways: First, we extend the network model to allow packets received on a link to arrive according to any process with an average rate, as opposed to the assumption of Poisson traffic with i.i.d. losses that was previously made. Second, in the case of Poisson traffic with i.i.d. losses, we derive error exponents that quantify the rate at which the probability of error decays with coding delay.
cs/0508049
Characterizations of Pseudo-Codewords of LDPC Codes
cs.IT cs.DM math.IT
An important property of high-performance, low complexity codes is the existence of highly efficient algorithms for their decoding. Many of the most efficient, recent graph-based algorithms, e.g. message passing algorithms and decoding based on linear programming, crucially depend on the efficient representation of a code in a graphical model. In order to understand the performance of these algorithms, we argue for the characterization of codes in terms of a so called fundamental cone in Euclidean space which is a function of a given parity check matrix of a code, rather than of the code itself. We give a number of properties of this fundamental cone derived from its connection to unramified covers of the graphical models on which the decoding algorithms operate. For the class of cycle codes, these developments naturally lead to a characterization of the fundamental polytope as the Newton polytope of the Hashimoto edge zeta function of the underlying graph.
cs/0508050
Duality between channel capacity and rate distortion with two-sided state information
cs.IT math.IT
We show that the duality between channel capacity and data compression is retained when state information is available to the sender, to the receiver, to both, or to neither. We present a unified theory for eight special cases of channel capacity and rate distortion with state information, which also extends existing results to arbitrary pairs of independent and identically distributed (i.i.d.) correlated state information available at the sender and at the receiver, respectively. In particular, the resulting general formula for channel capacity assumes the same form as the generalized Wyner Ziv rate distortion function.
cs/0508051
Trellis-Based Equalization for Sparse ISI Channels Revisited
cs.IT math.IT
Sparse intersymbol-interference (ISI) channels are encountered in a variety of high-data-rate communication systems. Such channels have a large channel memory length, but only a small number of significant channel coefficients. In this paper, trellis-based equalization of sparse ISI channels is revisited. Due to the large channel memory length, the complexity of maximum-likelihood detection, e.g., by means of the Viterbi algorithm (VA), is normally prohibitive. In the first part of the paper, a unified framework based on factor graphs is presented for complexity reduction without loss of optimality. In this new context, two known reduced-complexity algorithms for sparse ISI channels are recapitulated: The multi-trellis VA (M-VA) and the parallel-trellis VA (P-VA). It is shown that the M-VA, although claimed, does not lead to a reduced computational complexity. The P-VA, on the other hand, leads to a significant complexity reduction, but can only be applied for a certain class of sparse channels. In the second part of the paper, a unified approach is investigated to tackle general sparse channels: It is shown that the use of a linear filter at the receiver renders the application of standard reduced-state trellis-based equalizer algorithms feasible, without significant loss of optimality. Numerical results verify the efficiency of the proposed receiver structure.
cs/0508053
Measuring Semantic Similarity by Latent Relational Analysis
cs.LG cs.CL cs.IR
This paper introduces Latent Relational Analysis (LRA), a method for measuring semantic similarity. LRA measures similarity in the semantic relations between two pairs of words. When two pairs have a high degree of relational similarity, they are analogous. For example, the pair cat:meow is analogous to the pair dog:bark. There is evidence from cognitive science that relational similarity is fundamental to many cognitive and linguistic tasks (e.g., analogical reasoning). In the Vector Space Model (VSM) approach to measuring relational similarity, the similarity between two pairs is calculated by the cosine of the angle between the vectors that represent the two pairs. The elements in the vectors are based on the frequencies of manually constructed patterns in a large corpus. LRA extends the VSM approach in three ways: (1) patterns are derived automatically from the corpus, (2) Singular Value Decomposition is used to smooth the frequency data, and (3) synonyms are used to reformulate word pairs. This paper describes the LRA algorithm and experimentally compares LRA to VSM on two tasks, answering college-level multiple-choice word analogy questions and classifying semantic relations in noun-modifier expressions. LRA achieves state-of-the-art results, reaching human-level performance on the analogy questions and significantly exceeding VSM performance on both tasks.
cs/0508054
Sensing Capacity for Markov Random Fields
cs.IT math.IT
This paper computes the sensing capacity of a sensor network, with sensors of limited range, sensing a two-dimensional Markov random field, by modeling the sensing operation as an encoder. Sensor observations are dependent across sensors, and the sensor network output across different states of the environment is neither identically nor independently distributed. Using a random coding argument, based on the theory of types, we prove a lower bound on the sensing capacity of the network, which characterizes the ability of the sensor network to distinguish among environments with Markov structure, to within a desired accuracy.
cs/0508055
DNA Codes that Avoid Secondary Structures
cs.DM cs.IT math.IT
In this paper, we consider the problem of designing DNA sequences (codewords) for DNA storage systems and DNA computing that are unlikely to fold back onto themselves to form undesirable secondary structures. The paper addresses both the issue of enumerating the sequences with such properties and the problem of practical code construction.
cs/0508056
Very Simple Chaitin Machines for Concrete AIT
cs.IT math.IT
In 1975, Chaitin introduced his celebrated Omega number, the halting probability of a universal Chaitin machine, a universal Turing machine with a prefix-free domain. The Omega number's bits are {\em algorithmically random}--there is no reason the bits should be the way they are, if we define ``reason'' to be a computable explanation smaller than the data itself. Since that time, only {\em two} explicit universal Chaitin machines have been proposed, both by Chaitin himself. Concrete algorithmic information theory involves the study of particular universal Turing machines, about which one can state theorems with specific numerical bounds, rather than include terms like O(1). We present several new tiny Chaitin machines (those with a prefix-free domain) suitable for the study of concrete algorithmic information theory. One of the machines, which we call Keraia, is a binary encoding of lambda calculus based on a curried lambda operator. Source code is included in the appendices. We also give an algorithm for restricting the domain of blank-endmarker machines to a prefix-free domain over an alphabet that does not include the endmarker; this allows one to take many universal Turing machines and construct universal Chaitin machines from them.
cs/0508057
On the Performance of Turbo Codes in Quasi-Static Fading Channels
cs.IT math.IT
In this paper, we investigate in detail the performance of turbo codes in quasi-static fading channels both with and without antenna diversity. First, we develop a simple and accurate analytic technique to evaluate the performance of turbo codes in quasi-static fading channels. The proposed analytic technique relates the frame error rate of a turbo code to the iterative decoder convergence threshold, rather than to the turbo code distance spectrum. Subsequently, we compare the performance of various turbo codes in quasi-static fading channels. We show that, in contrast to the situation in the AWGN channel, turbo codes with different interleaver sizes or turbo codes based on RSC codes with different constraint lengths and generator polynomials exhibit identical performance. Moreover, we also compare the performance of turbo codes and convolutional codes in quasi-static fading channels under the condition of identical decoding complexity. In particular, we show that turbo codes do not outperform convolutional codes in quasi-static fading channels with no antenna diversity; and that turbo codes only outperform convolutional codes in quasi-static fading channels with antenna diversity.
cs/0508058
Entropy coding with Variable Length Re-writing Systems
cs.IT math.IT
This paper describes a new set of block source codes well suited for data compression. These codes are defined by sets of productions rules of the form a.l->b, where a in A represents a value from the source alphabet A and l, b are -small- sequences of bits. These codes naturally encompass other Variable Length Codes (VLCs) such as Huffman codes. It is shown that these codes may have a similar or even a shorter mean description length than Huffman codes for the same encoding and decoding complexity. A first code design method allowing to preserve the lexicographic order in the bit domain is described. The corresponding codes have the same mean description length (mdl) as Huffman codes from which they are constructed. Therefore, they outperform from a compression point of view the Hu-Tucker codes designed to offer the lexicographic property in the bit domain. A second construction method allows to obtain codes such that the marginal bit probability converges to 0.5 as the sequence length increases and this is achieved even if the probability distribution function is not known by the encoder.
cs/0508060
Algorithms for Discrete Denoising Under Channel Uncertainty
cs.IT math.IT
The goal of a denoising algorithm is to reconstruct a signal from its noise-corrupted observations. Perfect reconstruction is seldom possible and performance is measured under a given fidelity criterion. In a recent work, the authors addressed the problem of denoising unknown discrete signals corrupted by a discrete memoryless channel when the channel, rather than being completely known, is only known to lie in some uncertainty set of possible channels. A sequence of denoisers was derived for this case and shown to be asymptotically optimal with respect to a worst-case criterion argued most relevant to this setting. In the present work we address the implementation and complexity of this denoiser for channels parametrized by a scalar, establishing its practicality. We show that for symmetric channels, the problem can be mapped into a convex optimization problem, which can be solved efficiently. We also present empirical results suggesting the potential of these schemes to do well in practice. A key component of our schemes is an estimator of the subset of channels in the uncertainty set that are feasible in the sense of being able to give rise to the noise-corrupted signal statistics for some channel input distribution. We establish the efficiency of this estimator, both algorithmically and experimentally. We also present a modification of the recently developed discrete universal denoiser (DUDE) that assumes a channel based on the said estimator, and show that, in practice, the resulting scheme performs well. For concreteness, we focus on the binary alphabet case and binary symmetric channels, but also discuss the extensions of the algorithms to general finite alphabets and to general channels parameterized by a scalar.
cs/0508062
Decoding of Expander Codes at Rates Close to Capacity
cs.IT math.IT
The decoding error probability of codes is studied as a function of their block length. It is shown that the existence of codes with a polynomially small decoding error probability implies the existence of codes with an exponentially small decoding error probability. Specifically, it is assumed that there exists a family of codes of length N and rate R=(1-\epsilon)C (C is a capacity of a binary symmetric channel), whose decoding probability decreases polynomially in 1/N. It is shown that if the decoding probability decreases sufficiently fast, but still only polynomially fast in 1/N, then there exists another such family of codes whose decoding error probability decreases exponentially fast in N. Moreover, if the decoding time complexity of the assumed family of codes is polynomial in N and 1/\epsilon, then the decoding time complexity of the presented family is linear in N and polynomial in 1/\epsilon. These codes are compared to the recently presented codes of Barg and Zemor, ``Error Exponents of Expander Codes,'' IEEE Trans. Inform. Theory, 2002, and ``Concatenated Codes: Serial and Parallel,'' IEEE Trans. Inform. Theory, 2005. It is shown that the latter families can not be tuned to have exponentially decaying (in N) error probability, and at the same time to have decoding time complexity linear in N and polynomial in 1/\epsilon.
cs/0508064
Layered Orthogonal Lattice Detector for Two Transmit Antenna Communications
cs.IT math.IT
A novel detector for multiple-input multiple-output (MIMO) communications is presented. The algorithm belongs to the class of the lattice detectors, i.e. it finds a reduced complexity solution to the problem of finding the closest vector to the received observations. The algorithm achieves optimal maximum-likelihood (ML) performance in case of two transmit antennas, at the same time keeping a complexity much lower than the exhaustive search-based ML detection technique. Also, differently from the state-of-art lattice detector (namely sphere decoder), the proposed algorithm is suitable for a highly parallel hardware architecture and for a reliable bit soft-output information generation, thus making it a promising option for real-time high-data rate transmission.
cs/0508066
Can Small Museums Develop Compelling, Educational and Accessible Web Resources? The Case of Accademia Carrara
cs.MM cs.CY cs.DL cs.IR
Due to the lack of budget, competence, personnel and time, small museums are often unable to develop compelling, educational and accessible web resources for their permanent collections or temporary exhibitions. In an attempt to prove that investing in these types of resources can be very fruitful even for small institutions, we will illustrate the case of Accademia Carrara, a museum in Bergamo, northern Italy, which, for a current temporary exhibition on Cezanne and Renoir's masterpieces from the Paul Guillaume collection, developed a series of multimedia applications, including an accessible website, rich in content and educational material [www.cezannerenoir.it].
cs/0508068
Lossy source encoding via message-passing and decimation over generalized codewords of LDGM codes
cs.IT cs.AI math.IT
We describe message-passing and decimation approaches for lossy source coding using low-density generator matrix (LDGM) codes. In particular, this paper addresses the problem of encoding a Bernoulli(0.5) source: for randomly generated LDGM codes with suitably irregular degree distributions, our methods yield performance very close to the rate distortion limit over a range of rates. Our approach is inspired by the survey propagation (SP) algorithm, originally developed by Mezard et al. for solving random satisfiability problems. Previous work by Maneva et al. shows how SP can be understood as belief propagation (BP) for an alternative representation of satisfiability problems. In analogy to this connection, our approach is to define a family of Markov random fields over generalized codewords, from which local message-passing rules can be derived in the standard way. The overall source encoding method is based on message-passing, setting a subset of bits to their preferred values (decimation), and reducing the code.
cs/0508070
MAP estimation via agreement on (hyper)trees: Message-passing and linear programming
cs.IT cs.AI math.IT
We develop and analyze methods for computing provably optimal {\em maximum a posteriori} (MAP) configurations for a subclass of Markov random fields defined on graphs with cycles. By decomposing the original distribution into a convex combination of tree-structured distributions, we obtain an upper bound on the optimal value of the original problem (i.e., the log probability of the MAP assignment) in terms of the combined optimal values of the tree problems. We prove that this upper bound is tight if and only if all the tree distributions share an optimal configuration in common. An important implication is that any such shared configuration must also be a MAP configuration for the original distribution. Next we develop two approaches to attempting to obtain tight upper bounds: (a) a {\em tree-relaxed linear program} (LP), which is derived from the Lagrangian dual of the upper bounds; and (b) a {\em tree-reweighted max-product message-passing algorithm} that is related to but distinct from the max-product algorithm. In this way, we establish a connection between a certain LP relaxation of the mode-finding problem, and a reweighted form of the max-product (min-sum) message-passing algorithm.
cs/0508072
On Achievable Rates and Complexity of LDPC Codes for Parallel Channels with Application to Puncturing
cs.IT math.IT
This paper considers the achievable rates and decoding complexity of low-density parity-check (LDPC) codes over statistically independent parallel channels. The paper starts with the derivation of bounds on the conditional entropy of the transmitted codeword given the received sequence at the output of the parallel channels; the component channels are considered to be memoryless, binary-input, and output-symmetric (MBIOS). These results serve for the derivation of an upper bound on the achievable rates of ensembles of LDPC codes under optimal maximum-likelihood (ML) decoding when their transmission takes place over parallel MBIOS channels. The paper relies on the latter bound for obtaining upper bounds on the achievable rates of ensembles of randomly and intentionally punctured LDPC codes over MBIOS channels. The paper also provides a lower bound on the decoding complexity (per iteration) of ensembles of LDPC codes under message-passing iterative decoding over parallel MBIOS channels; the bound is given in terms of the gap between the rate of these codes for which reliable communication is achievable and the channel capacity. The paper presents a diagram which shows interconnections between the theorems introduced in this paper and some other previously reported results. The setting which serves for the derivation of the bounds on the achievable rates and decoding complexity is general, and the bounds can be applied to other scenarios which can be treated as different forms of communication over parallel channels.
cs/0508073
Universal Learning of Repeated Matrix Games
cs.LG cs.AI
We study and compare the learning dynamics of two universal learning algorithms, one based on Bayesian learning and the other on prediction with expert advice. Both approaches have strong asymptotic performance guarantees. When confronted with the task of finding good long-term strategies in repeated 2x2 matrix games, they behave quite differently.
cs/0508074
Throughput and Delay in Random Wireless Networks with Restricted Mobility
cs.IT cs.NI math.IT
Grossglauser and Tse (2001) introduced a mobile random network model where each node moves independently on a unit disk according to a stationary uniform distribution and showed that a throughput of $\Theta(1)$ is achievable. El Gamal, Mammen, Prabhakar and Shah (2004) showed that the delay associated with this throughput scales as $\Theta(n\log n)$, when each node moves according to an independent random walk. In a later work, Diggavi, Grossglauser and Tse (2002) considered a random network on a sphere with a restricted mobility model, where each node moves along a randomly chosen great circle on the unit sphere. They showed that even with this one-dimensional restriction on mobility, constant throughput scaling is achievable. Thus, this particular mobility restriction does not affect the throughput scaling. This raises the question whether this mobility restriction affects the delay scaling. This paper studies the delay scaling at $\Theta(1)$ throughput for a random network with restricted mobility. First, a variant of the scheme presented by Diggavi, Grossglauser and Tse (2002) is presented and it is shown to achieve $\Theta(1)$ throughput using different (and perhaps simpler) techniques. The exact order of delay scaling for this scheme is determined, somewhat surprisingly, to be of $\Theta(n\log n)$, which is the same as that without the mobility restriction. Thus, this particular mobility restriction \emph{does not} affect either the maximal throughput scaling or the corresponding delay scaling of the network. This happens because under this 1-D restriction, each node is in the proximity of every other node in essentially the same manner as without this restriction.
cs/0508075
Complexity of Networks
cs.IT math.IT
Network or graph structures are ubiquitous in the study of complex systems. Often, we are interested in complexity trends of these system as it evolves under some dynamic. An example might be looking at the complexity of a food web as species enter an ecosystem via migration or speciation, and leave via extinction. In this paper, a complexity measure of networks is proposed based on the {\em complexity is information content} paradigm. To apply this paradigm to any object, one must fix two things: a representation language, in which strings of symbols from some alphabet describe, or stand for the objects being considered; and a means of determining when two such descriptions refer to the same object. With these two things set, the information content of an object can be computed in principle from the number of equivalent descriptions describing a particular object. I propose a simple representation language for undirected graphs that can be encoded as a bitstring, and equivalence is a topological equivalence. I also present an algorithm for computing the complexity of an arbitrary undirected network.
cs/0508076
Myopic Coding in Multiple Relay Channels
cs.IT math.IT
In this paper, we investigate achievable rates for data transmission from sources to sinks through multiple relay networks. We consider myopic coding, a constrained communication strategy in which each node has only a local view of the network, meaning that nodes can only transmit to and decode from neighboring nodes. We compare this with omniscient coding, in which every node has a global view of the network and all nodes can cooperate. Using Gaussian channels as examples, we find that when the nodes transmit at low power, the rates achievable with two-hop myopic coding are as large as that under omniscient coding in a five-node multiple relay channel and close to that under omniscient coding in a six-node multiple relay channel. These results suggest that we may do local coding and cooperation without compromising much on the transmission rate. Practically, myopic coding schemes are more robust to topology changes because encoding and decoding at a node are not affected when there are changes at remote nodes. Furthermore, myopic coding mitigates the high computational complexity and large buffer/memory requirements of omniscient coding.
cs/0508077
Families of unitary matrices achieving full diversity
cs.IT math.IT
This paper presents an algebraic construction of families of unitary matrices that achieve full diversity. They are obtained as subsets of cyclic division algebras.
cs/0508083
A General Framework for Codes Involving Redundancy Minimization
cs.IT cs.DS math.IT
A framework with two scalar parameters is introduced for various problems of finding a prefix code minimizing a coding penalty function. The framework encompasses problems previously proposed by Huffman, Campbell, Nath, and Drmota and Szpankowski, shedding light on the relationships among these problems. In particular, Nath's range of problems can be seen as bridging the minimum average redundancy problem of Huffman with the minimum maximum pointwise redundancy problem of Drmota and Szpankowski. Using this framework, two linear-time Huffman-like algorithms are devised for the minimum maximum pointwise redundancy problem, the only one in the framework not previously solved with a Huffman-like algorithm. Both algorithms provide solutions common to this problem and a subrange of Nath's problems, the second algorithm being distinguished by its ability to find the minimum variance solution among all solutions common to the minimum maximum pointwise redundancy and Nath problems. Simple redundancy bounds are also presented.
cs/0508084
Source Coding for Quasiarithmetic Penalties
cs.IT cs.DS math.IT
Huffman coding finds a prefix code that minimizes mean codeword length for a given probability distribution over a finite number of items. Campbell generalized the Huffman problem to a family of problems in which the goal is to minimize not mean codeword length but rather a generalized mean known as a quasiarithmetic or quasilinear mean. Such generalized means have a number of diverse applications, including applications in queueing. Several quasiarithmetic-mean problems have novel simple redundancy bounds in terms of a generalized entropy. A related property involves the existence of optimal codes: For ``well-behaved'' cost functions, optimal codes always exist for (possibly infinite-alphabet) sources having finite generalized entropy. Solving finite instances of such problems is done by generalizing an algorithm for finding length-limited binary codes to a new algorithm for finding optimal binary codes for any quasiarithmetic mean with a convex cost function. This algorithm can be performed using quadratic time and linear space, and can be extended to other penalty functions, some of which are solvable with similar space and time complexity, and others of which are solvable with slightly greater complexity. This reduces the computational complexity of a problem involving minimum delay in a queue, allows combinations of previously considered problems to be optimized, and greatly expands the space of problems solvable in quadratic time and linear space. The algorithm can be extended for purposes such as breaking ties among possibly different optimal codes, as with bottom-merge Huffman coding.