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cs/0508085
On the Asymptotic Performance of Iterative Decoders for Product Codes
cs.IT cs.DM math.IT
We consider hard-decision iterative decoders for product codes over the erasure channel, which employ repeated rounds of decoding rows and columns alternatingly. We derive the exact asymptotic probability of decoding failure as a function of the error-correction capabilities of the row and column codes, the number of decoding rounds, and the channel erasure probability. We examine both the case of codes capable of correcting a constant amount of errors, and the case of codes capable of correcting a constant fraction of their length.
cs/0508088
Special Cases of Encodings by Generalized Adaptive Codes
cs.IT math.IT
Adaptive (variable-length) codes associate variable-length codewords to symbols being encoded depending on the previous symbols in the input data string. This class of codes has been presented in [Dragos Trinca, cs.DS/0505007] as a new class of non-standard variable-length codes. Generalized adaptive codes (GA codes, for short) have been also presented in [Dragos Trinca, cs.DS/0505007] not only as a new class of non-standard variable-length codes, but also as a natural generalization of adaptive codes of any order. This paper is intended to continue developing the theory of variable-length codes by establishing several interesting connections between adaptive codes and other classes of codes. The connections are discussed not only from a theoretical point of view (by proving new results), but also from an applicative one (by proposing several applications). First, we prove that adaptive Huffman encodings and Lempel-Ziv encodings are particular cases of encodings by GA codes. Second, we show that any (n,1,m) convolutional code satisfying certain conditions can be modelled as an adaptive code of order m. Third, we describe a cryptographic scheme based on the connection between adaptive codes and convolutional codes, and present an insightful analysis of this scheme. Finally, we conclude by generalizing adaptive codes to (p,q)-adaptive codes, and discussing connections between adaptive codes and time-varying codes.
cs/0508092
Summarizing Reports on Evolving Events; Part I: Linear Evolution
cs.CL cs.IR
We present an approach for summarization from multiple documents which report on events that evolve through time, taking into account the different document sources. We distinguish the evolution of an event into linear and non-linear. According to our approach, each document is represented by a collection of messages which are then used in order to instantiate the cross-document relations that determine the summary content. The paper presents the summarization system that implements this approach through a case study on linear evolution.
cs/0508093
Performance of PPM Multipath Synchronization in the Limit of Large Bandwidth
cs.IT math.IT
The acquisition, or synchronization, of the multipath profile for an ultrawideband pulse position modulation (PPM) communication systems is considered. Synchronization is critical for the proper operation of PPM based For the multipath channel, it is assumed that channel gains are known, but path delays are unknown. In the limit of large bandwidth, W, it is assumed that the number of paths, L, grows. The delay spread of the channel, M, is proportional to the bandwidth. The rate of growth of L versus M determines whether synchronization can occur. It is shown that if L/sqrt(M) --> 0, then the maximum likelihood synchronizer cannot acquire any of the paths and alternatively if L/M --> 0, the maximum likelihood synchronizer is guaranteed to miss at least one path.
cs/0508094
Conference Key Agreement and Quantum Sharing of Classical Secrets with Noisy GHZ States
cs.IT cs.CR math.IT
We propose a wide class of distillation schemes for multi-partite entangled states that are CSS-states. Our proposal provides not only superior efficiency, but also new insights on the connection between CSS-states and bipartite graph states. We then consider the applications of our distillation schemes for two cryptographic tasks--namely, (a) conference key agreement and (b) quantum sharing of classical secrets. In particular, we construct ``prepare-and-measure'' protocols. Also we study the yield of those protocols and the threshold value of the fidelity above which the protocols can function securely. Surprisingly, our protocols will function securely even when the initial state does not violate the standard Bell-inequalities for GHZ states. Experimental realization involving only bi-partite entanglement is also suggested.
cs/0508095
Capacity of Ultra Wide Band Wireless Ad Hoc Networks
cs.IT cs.NI math.IT
Throughput capacity is a critical parameter for the design and evaluation of ad-hoc wireless networks. Consider n identical randomly located nodes, on a unit area, forming an ad-hoc wireless network. Assuming a fixed per node transmission capability of T bits per second at a fixed range, it has been shown that the uniform throughput capacity per node r(n) is Theta((T)/(sqrt{n log n})), a decreasing function of node density n. However an alternate communication model may also be considered, with each node constrained to a maximum transmit power P_0 and capable of utilizing W Hz of bandwidth. Under the limiting case W rightarrow infinity, such as in Ultra Wide Band (UWB) networks, the uniform throughput per node is O ((n log n)^{(alpha-1}/2}) (upper bound) and Omega((n^{(alpha-1)/2})/((log n)^{(alpha +1)/2})) (achievable lower bound). These bounds demonstrate that throughput increases with node density $n$, in contrast to previously published results. This is the result of the large bandwidth, and the assumed power and rate adaptation, which alleviate interference. Thus, the effect of physical layer properties on the capacity of ad hoc wireless networks is demonstrated. Further, the promise of UWB as a physical layer technology for ad-hoc networks is justified.
cs/0508096
On Multiple User Channels with Causal State Information at the Transmitters
cs.IT math.IT
We extend Shannon's result on the capacity of channels with state information to multiple user channels. More specifically, we characterize the capacity (region) of degraded broadcast channels and physically degraded relay channels where the channel state information is causally available at the transmitters. We also obtain inner and outer bounds on the capacity region for multiple access channels with causal state information at the transmitters.
cs/0508098
An Explicit Construction of Universally Decodable Matrices
cs.IT cs.DM math.IT
Universally decodable matrices can be used for coding purposes when transmitting over slow fading channels. These matrices are parameterized by positive integers $L$ and $n$ and a prime power $q$. Based on Pascal's triangle we give an explicit construction of universally decodable matrices for any non-zero integers $L$ and $n$ and any prime power $q$ where $L \leq q+1$. This is the largest set of possible parameter values since for any list of universally decodable matrices the value $L$ is upper bounded by $q+1$, except for the trivial case $n = 1$. For the proof of our construction we use properties of Hasse derivatives, and it turns out that our construction has connections to Reed-Solomon codes, Reed-Muller codes, and so-called repeated-root cyclic codes. Additionally, we show how universally decodable matrices can be modified so that they remain universally decodable matrices.
cs/0508099
Search Process and Probabilistic Bifix Approach
cs.IT cs.CV math.IT
An analytical approach to a search process is a mathematical prerequisite for digital synchronization acquisition analysis and optimization. A search is performed for an arbitrary set of sequences within random but not equiprobable L-ary data. This paper derives in detail an expression for probability distribution function, from which other statistical parameters - expected value and variance - can be obtained. The probabilistic nature of (cross-) bifix indicators is shown and application examples are outlined, ranging beyond the usual telecommunication field.
cs/0508100
A primer on Answer Set Programming
cs.AI cs.LO
A introduction to the syntax and Semantics of Answer Set Programming intended as an handout to [under]graduate students taking Artificial Intlligence or Logic Programming classes.
cs/0508101
Maximum Weight Matching via Max-Product Belief Propagation
cs.IT cs.AI math.IT
Max-product "belief propagation" is an iterative, local, message-passing algorithm for finding the maximum a posteriori (MAP) assignment of a discrete probability distribution specified by a graphical model. Despite the spectacular success of the algorithm in many application areas such as iterative decoding, computer vision and combinatorial optimization which involve graphs with many cycles, theoretical results about both correctness and convergence of the algorithm are known in few cases (Weiss-Freeman Wainwright, Yeddidia-Weiss-Freeman, Richardson-Urbanke}. In this paper we consider the problem of finding the Maximum Weight Matching (MWM) in a weighted complete bipartite graph. We define a probability distribution on the bipartite graph whose MAP assignment corresponds to the MWM. We use the max-product algorithm for finding the MAP of this distribution or equivalently, the MWM on the bipartite graph. Even though the underlying bipartite graph has many short cycles, we find that surprisingly, the max-product algorithm always converges to the correct MAP assignment as long as the MAP assignment is unique. We provide a bound on the number of iterations required by the algorithm and evaluate the computational cost of the algorithm. We find that for a graph of size $n$, the computational cost of the algorithm scales as $O(n^3)$, which is the same as the computational cost of the best known algorithm. Finally, we establish the precise relation between the max-product algorithm and the celebrated {\em auction} algorithm proposed by Bertsekas. This suggests possible connections between dual algorithm and max-product algorithm for discrete optimization problems.
cs/0508102
Investigations of Process Damping Forces in Metal Cutting
cs.CE
Using finite element software developed for metal cutting by Third Wave Systems we investigate the forces involved in chatter, a self-sustained oscillation of the cutting tool. The phenomena is decomposed into a vibrating tool cutting a flat surface work piece, and motionless tool cutting a work piece with a wavy surface. While cutting the wavy surface, the shearplane was seen to oscillate in advance of the oscillation of the depth of cut, as were the cutting, thrust, and shear plane forces. The vibrating tool was used to investigate process damping through the interaction of the relief face of the tool and the workpiece. Crushing forces are isolated and compared to the contact length between the tool and workpiece. We found that the wavelength dependence of the forces depended on the relative size of the wavelength to the length of the relief face of the tool. The results indicate that the damping force from crushing will be proportional to the cutting speed for short tools, and inversely proportional for long tools.
cs/0508103
Corpus-based Learning of Analogies and Semantic Relations
cs.LG cs.CL cs.IR
We present an algorithm for learning from unlabeled text, based on the Vector Space Model (VSM) of information retrieval, that can solve verbal analogy questions of the kind found in the SAT college entrance exam. A verbal analogy has the form A:B::C:D, meaning "A is to B as C is to D"; for example, mason:stone::carpenter:wood. SAT analogy questions provide a word pair, A:B, and the problem is to select the most analogous word pair, C:D, from a set of five choices. The VSM algorithm correctly answers 47% of a collection of 374 college-level analogy questions (random guessing would yield 20% correct; the average college-bound senior high school student answers about 57% correctly). We motivate this research by applying it to a difficult problem in natural language processing, determining semantic relations in noun-modifier pairs. The problem is to classify a noun-modifier pair, such as "laser printer", according to the semantic relation between the noun (printer) and the modifier (laser). We use a supervised nearest-neighbour algorithm that assigns a class to a given noun-modifier pair by finding the most analogous noun-modifier pair in the training data. With 30 classes of semantic relations, on a collection of 600 labeled noun-modifier pairs, the learning algorithm attains an F value of 26.5% (random guessing: 3.3%). With 5 classes of semantic relations, the F value is 43.2% (random: 20%). The performance is state-of-the-art for both verbal analogies and noun-modifier relations.
cs/0508104
A Generalised Hadamard Transform
cs.IT cs.DM math.IT
A Generalised Hadamard Transform for multi-phase or multilevel signals is introduced, which includes the Fourier, Generalised, Discrete Fourier, Walsh-Hadamard and Reverse Jacket Transforms. The jacket construction is formalised and shown to admit a tensor product decomposition. Primary matrices under this decomposition are identified. New examples of primary jacket matrices of orders 8 and 12 are presented.
cs/0508107
New Upper Bounds on A(n,d)
cs.IT cs.DM math.IT
Upper bounds on the maximum number of codewords in a binary code of a given length and minimum Hamming distance are considered. New bounds are derived by a combination of linear programming and counting arguments. Some of these bounds improve on the best known analytic bounds. Several new record bounds are obtained for codes with small lengths.
cs/0508114
A Family of Binary Sequences with Optimal Correlation Property and Large Linear Span
cs.CR cs.IT math.IT
A family of binary sequences is presented and proved to have optimal correlation property and large linear span. It includes the small set of Kasami sequences, No sequence set and TN sequence set as special cases. An explicit lower bound expression on the linear span of sequences in the family is given. With suitable choices of parameters, it is proved that the family has exponentially larger linear spans than both No sequences and TN sequences. A class of ideal autocorrelation sequences is also constructed and proved to have large linear span.
cs/0508115
New Sequence Sets with Zero-Correlation Zone
cs.IT math.IT
A method for constructing sets of sequences with zero-correlation zone (ZCZ sequences) and sequence sets with low cross correlation is proposed. The method is to use families of short sequences and complete orthogonal sequence sets to derive families of long sequences with desired correlation properties. It is a unification of works of Matsufuji and Torii \emph{et al.}, and there are more choices of parameters of sets for our method. In particular, ZCZ sequence sets generated by the method can achieve a related ZCZ bound. Furthermore, the proposed method can be utilized to derive new ZCZ sets with both longer ZCZ and larger set size from known ZCZ sets. These sequence sets are applicable in broadband satellite IP networks.
cs/0508117
Long-term neuronal behavior caused by two synaptic modification mechanisms
cs.NE cs.CE
We report the first results of simulating the coupling of neuronal, astrocyte, and cerebrovascular activity. It is suggested that the dynamics of the system is different from systems that only include neurons. In the neuron-vascular coupling, distribution of synapse strengths affects neuronal behavior and thus balance of the blood flow; oscillations are induced in the neuron-to-astrocyte coupling.
cs/0508118
Unified Theory of Source Coding: Part I -- Two Terminal Problems
cs.IT math.IT
Since the publication of Shannon's theory of one terminal source coding, a number of interesting extensions have been derived by researchers such as Slepian-Wolf, Wyner, Ahlswede-K\"{o}rner, Wyner-Ziv and Berger-Yeung. Specifically, the achievable rate or rate-distortion region has been described by a first order information-theoretic functional of the source statistics in each of the above cases. At the same time several problems have also remained unsolved. Notable two terminal examples include the joint distortion problem, where both sources are reconstructed under a combined distortion criterion, as well as the partial side information problem, where one source is reconstructed under a distortion criterion using information about the other (side information) available at a certain rate (partially). In this paper we solve both of these open problems. Specifically, we give an infinite order description of the achievable rate-distortion region in each case. In our analysis we set the above problems in a general framework and formulate a unified methodology that solves not only the problems at hand but any two terminal problem with noncooperative encoding. The key to such unification is held by a fundamental source coding principle which we derive by extending the typicality arguments of Shannon and Wyner-Ziv. Finally, we demonstrate the expansive scope of our technique by re-deriving known coding theorems. We shall observe that our infinite order descriptions simplify to the expected first order in the known special cases.
cs/0508119
Unified Theory of Source Coding: Part II -- Multiterminal Problems
cs.IT math.IT
In the first paper of this two part communication, we solved in a unified framework a variety of two terminal source coding problems with noncooperative encoders, thereby consolidating works of Shannon, Slepian-Wolf, Wyner, Ahlswede-K\"{o}rner, Wyner-Ziv, Berger {\em et al.} and Berger-Yeung. To achieve such unification we made use of a fundamental principle that dissociates bulk of the analysis from the distortion criterion at hand (if any) and extends the typicality arguments of Shannon and Wyner-Ziv. In this second paper, we generalize the fundamental principle for any number of sources and on its basis exhaustively solve all multiterminal source coding problems with noncooperative encoders and one decoder. The distortion criteria, when applicable, are required to apply to single letters and be bounded. Our analysis includes cases where side information is, respectively, partially available, completely available and altogether unavailable at the decoder. As seen in our first paper, the achievable regions permit infinite order information-theoretic descriptions. We also show that the entropy-constrained multiterminal estimation problem can be solved as a special case of our theory.
cs/0508120
Iterative Algorithm for Finding Frequent Patterns in Transactional Databases
cs.DB
A high-performance algorithm for searching for frequent patterns (FPs) in transactional databases is presented. The search for FPs is carried out by using an iterative sieve algorithm by computing the set of enclosed cycles. In each inner cycle of level FPs composed of elements are generated. The assigned number of enclosed cycles (the parameter of the problem) defines the maximum length of the desired FPs. The efficiency of the algorithm is produced by (i) the extremely simple logical searching scheme, (ii) the avoidance of recursive procedures, and (iii) the usage of only one-dimensional arrays of integers.
cs/0508121
How Good is Phase-Shift Keying for Peak-Limited Rayleigh Fading Channels in the Low-SNR Regime?
cs.IT math.IT
This paper investigates the achievable information rate of phase-shift keying (PSK) over frequency non-selective Rayleigh fading channels without channel state information (CSI). The fading process exhibits general temporal correlation characterized by its spectral density function. We consider both discrete-time and continuous-time channels, and find their asymptotics at low signal-to-noise ratio (SNR). Compared to known capacity upper bounds under peak constraints, these asymptotics usually lead to negligible rate loss in the low-SNR regime for slowly time-varying fading channels. We further specialize to case studies of Gauss-Markov and Clarke's fading models.
cs/0508122
Streaming and Sublinear Approximation of Entropy and Information Distances
cs.DS cs.IT math.IT
In many problems in data mining and machine learning, data items that need to be clustered or classified are not points in a high-dimensional space, but are distributions (points on a high dimensional simplex). For distributions, natural measures of distance are not the $\ell_p$ norms and variants, but information-theoretic measures like the Kullback-Leibler distance, the Hellinger distance, and others. Efficient estimation of these distances is a key component in algorithms for manipulating distributions. Thus, sublinear resource constraints, either in time (property testing) or space (streaming) are crucial. We start by resolving two open questions regarding property testing of distributions. Firstly, we show a tight bound for estimating bounded, symmetric f-divergences between distributions in a general property testing (sublinear time) framework (the so-called combined oracle model). This yields optimal algorithms for estimating such well known distances as the Jensen-Shannon divergence and the Hellinger distance. Secondly, we close a $(\log n)/H$ gap between upper and lower bounds for estimating entropy $H$ in this model. In a stream setting (sublinear space), we give the first algorithm for estimating the entropy of a distribution. Our algorithm runs in polylogarithmic space and yields an asymptotic constant factor approximation scheme. We also provide other results along the space/time/approximation tradeoff curve.
cs/0508124
Coding Schemes for Line Networks
cs.IT cs.DC cs.NI math.IT
We consider a simple network, where a source and destination node are connected with a line of erasure channels. It is well known that in order to achieve the min-cut capacity, the intermediate nodes are required to process the information. We propose coding schemes for this setting, and discuss each scheme in terms of complexity, delay, achievable rate, memory requirement, and adaptability to unknown channel parameters. We also briefly discuss how these schemes can be extended to more general networks.
cs/0508126
A Closed-Form Solution for the Finite Length Constant Modulus Receiver
cs.GT cs.IT math.IT
In this paper, a closed-form solution minimizing the Godard or Constant Modulus (CM) cost function under the practical conditions of finite SNR and finite equalizer length is derived. While previous work has been reported by Zeng et al., IEEE Trans. Information Theory. 1998, to establish the link between the constant modulus and Wiener receivers, we show that under the Gaussian approximation of intersymbol interference at the output of the equalizer, the CM finite-length receiver is equivalent to the nonblind MMSE equalizer up to a complex gain factor. Some simulation results are provided to support the Gaussian approximation assumption.
cs/0508127
On context-tree prediction of individual sequences
cs.IT math.IT
Motivated by the evident success of context-tree based methods in lossless data compression, we explore, in this paper, methods of the same spirit in universal prediction of individual sequences. By context-tree prediction, we refer to a family of prediction schemes, where at each time instant $t$, after having observed all outcomes of the data sequence $x_1,...,x_{t-1}$, but not yet $x_t$, the prediction is based on a ``context'' (or a state) that consists of the $k$ most recent past outcomes $x_{t-k},...,x_{t-1}$, where the choice of $k$ may depend on the contents of a possibly longer, though limited, portion of the observed past, $x_{t-k_{\max}},...x_{t-1}$. This is different from the study reported in [1], where general finite-state predictors as well as ``Markov'' (finite-memory) predictors of fixed order, were studied in the regime of individual sequences. Another important difference between this study and [1] is the asymptotic regime. While in [1], the resources of the predictor (i.e., the number of states or the memory size) were kept fixed regardless of the length $N$ of the data sequence, here we investigate situations where the number of contexts or states is allowed to grow concurrently with $N$. We are primarily interested in the following fundamental question: What is the critical growth rate of the number of contexts, below which the performance of the best context-tree predictor is still universally achievable, but above which it is not? We show that this critical growth rate is linear in $N$. In particular, we propose a universal context-tree algorithm that essentially achieves optimum performance as long as the growth rate is sublinear, and show that, on the other hand, this is impossible in the linear case.
cs/0508129
Temporal Phylogenetic Networks and Logic Programming
cs.LO cs.AI cs.PL
The concept of a temporal phylogenetic network is a mathematical model of evolution of a family of natural languages. It takes into account the fact that languages can trade their characteristics with each other when linguistic communities are in contact, and also that a contact is only possible when the languages are spoken at the same time. We show how computational methods of answer set programming and constraint logic programming can be used to generate plausible conjectures about contacts between prehistoric linguistic communities, and illustrate our approach by applying it to the evolutionary history of Indo-European languages. To appear in Theory and Practice of Logic Programming (TPLP).
cs/0508130
A Fresh Look at the Reliability of Long-term Digital Storage
cs.DL cs.DB cs.OS
Many emerging Web services, such as email, photo sharing, and web site archives, need to preserve large amounts of quickly-accessible data indefinitely into the future. In this paper, we make the case that these applications' demands on large scale storage systems over long time horizons require us to re-evaluate traditional storage system designs. We examine threats to long-lived data from an end-to-end perspective, taking into account not just hardware and software faults but also faults due to humans and organizations. We present a simple model of long-term storage failures that helps us reason about the various strategies for addressing these threats in a cost-effective manner. Using this model we show that the most important strategies for increasing the reliability of long-term storage are detecting latent faults quickly, automating fault repair to make it faster and cheaper, and increasing the independence of data replicas.
cs/0508132
Planning with Preferences using Logic Programming
cs.AI
We present a declarative language, PP, for the high-level specification of preferences between possible solutions (or trajectories) of a planning problem. This novel language allows users to elegantly express non-trivial, multi-dimensional preferences and priorities over such preferences. The semantics of PP allows the identification of most preferred trajectories for a given goal. We also provide an answer set programming implementation of planning problems with PP preferences.
cs/0509001
Asymptotic Behavior of Error Exponents in the Wideband Regime
cs.IT math.IT
In this paper, we complement Verd\'{u}'s work on spectral efficiency in the wideband regime by investigating the fundamental tradeoff between rate and bandwidth when a constraint is imposed on the error exponent. Specifically, we consider both AWGN and Rayleigh-fading channels. For the AWGN channel model, the optimal values of $R_z(0)$ and $\dot{R_z}(0)$ are calculated, where $R_z(1/B)$ is the maximum rate at which information can be transmitted over a channel with bandwidth $B/2$ when the error-exponent is constrained to be greater than or equal to $z.$ Based on this calculation, we say that a sequence of input distributions is near optimal if both $R_z(0)$ and $\dot{R_z}(0)$ are achieved. We show that QPSK, a widely-used signaling scheme, is near-optimal within a large class of input distributions for the AWGN channel. Similar results are also established for a fading channel where full CSI is available at the receiver.
cs/0509002
Component Based Programming in Scientific Computing: The Viable Approach
cs.CE
Computational scientists are facing a new era where the old ways of developing and reusing code have to be left behind and a few daring steps are to be made towards new horizons. The present work analyzes the needs that drive this change, the factors that contribute to the inertia of the community and slow the transition, the status and perspective of present attempts, the principle, practical and technical problems that are to be addressed in the short and long run.
cs/0509003
COMODI: Architecture for a Component-Based Scientific Computing System
cs.CE
The COmputational MODule Integrator (COMODI) is an initiative aiming at a component based framework, component developer tool and component repository for scientific computing. We identify the main ingredients to a solution that would be sufficiently appealing to scientists and engineers to consider alternatives to their deeply rooted programming traditions. The overall structure of the complete solution is sketched with special emphasis on the Component Developer Tool standing at the basis of COMODI.
cs/0509005
Combining Structured Corporate Data and Document Content to Improve Expertise Finding
cs.IR
In this paper, we present an algorithm for automatically building expertise evidence for finding experts within an organization by combining structured corporate information with different content. We also describe our test data collection and our evaluation method. Evaluation of the algorithm shows that using organizational structure leads to a significant improvement in the precision of finding an expert. Furthermore we evaluate the impact of using different data sources on the quality of the results and conclude that Expert Finding is not a "one engine fits all" solution. It requires an analysis of the information space into which a solution will be placed and the appropriate selection and weighting scheme of the data sources.
cs/0509006
Optimal space-time codes for the MIMO amplify-and-forward cooperative channel
cs.IT math.IT
In this work, we extend the non-orthogonal amplify-and-forward (NAF) cooperative diversity scheme to the MIMO channel. A family of space-time block codes for a half-duplex MIMO NAF fading cooperative channel with N relays is constructed. The code construction is based on the non-vanishing determinant criterion (NVD) and is shown to achieve the optimal diversity-multiplexing tradeoff (DMT) of the channel. We provide a general explicit algebraic construction, followed by some examples. In particular, in the single relay case, it is proved that the Golden code and the 4x4 Perfect code are optimal for the single-antenna and two-antenna case, respectively. Simulation results reveal that a significant gain (up to 10dB) can be obtained with the proposed codes, especially in the single-antenna case.
cs/0509007
Non-Data-Aided Parameter Estimation in an Additive White Gaussian Noise Channel
cs.IT math.IT
Non-data-aided (NDA) parameter estimation is considered for binary-phase-shift-keying transmission in an additive white Gaussian noise channel. Cramer-Rao lower bounds (CRLBs) for signal amplitude, noise variance, channel reliability constant and bit-error rate are derived and it is shown how these parameters relate to the signal-to-noise ratio (SNR). An alternative derivation of the iterative maximum likelihood (ML) SNR estimator is presented together with a novel, low complexity NDA SNR estimator. The performance of the proposed estimator is compared to previously suggested estimators and the CRLB. The results show that the proposed estimator performs close to the iterative ML estimator at significantly lower computational complexity.
cs/0509008
Joint Equalization and Decoding for Nonlinear Two-Dimensional Intersymbol Interference Channels with Application to Optical Storage
cs.IT math.IT
An algorithm that performs joint equalization and decoding for nonlinear two-dimensional intersymbol interference channels is presented. The algorithm performs sum-product message-passing on a factor graph that represents the underlying system. The two-dimensional optical storage (TWODOS) technology is an example of a system with nonlinear two-dimensional intersymbol interference. Simulations for the nonlinear channel model of TWODOS show significant improvement in performance over uncoded performance. Noise tolerance thresholds for the algorithm for the TWODOS channel, computed using density evolution, are also presented and accurately predict the limiting performance of the algorithm as the codeword length increases.
cs/0509009
Joint Equalization and Decoding for Nonlinear Two-Dimensional Intersymbol Interference Channels
cs.IT math.IT
An algorithm that performs joint equalization and decoding for channels with nonlinear two-dimensional intersymbol interference is presented. The algorithm performs sum-product message-passing on a factor graph that represents the underlying system. The two-dimensional optical storage (TwoDOS) technology is an example of a system with nonlinear two-dimensional intersymbol interference. Simulations for the nonlinear channel model of TwoDOS show significant improvement in performance over uncoded performance. Noise tolerance thresholds for the TwoDOS channel computed using density evolution are also presented.
cs/0509010
Minimum Mean-Square-Error Equalization using Priors for Two-Dimensional Intersymbol Interference
cs.IT math.IT
Joint equalization and decoding schemes are described for two-dimensional intersymbol interference (ISI) channels. Equalization is performed using the minimum mean-square-error (MMSE) criterion. Low-density parity-check codes are used for error correction. The MMSE schemes are the extension of those proposed by Tuechler et al. (2002) for one-dimensional ISI channels. Extrinsic information transfer charts, density evolution, and bit-error rate versus signal-to-noise ratio curves are used to study the performance of the schemes.
cs/0509011
Clustering Mixed Numeric and Categorical Data: A Cluster Ensemble Approach
cs.AI
Clustering is a widely used technique in data mining applications for discovering patterns in underlying data. Most traditional clustering algorithms are limited to handling datasets that contain either numeric or categorical attributes. However, datasets with mixed types of attributes are common in real life data mining applications. In this paper, we propose a novel divide-and-conquer technique to solve this problem. First, the original mixed dataset is divided into two sub-datasets: the pure categorical dataset and the pure numeric dataset. Next, existing well established clustering algorithms designed for different types of datasets are employed to produce corresponding clusters. Last, the clustering results on the categorical and numeric dataset are combined as a categorical dataset, on which the categorical data clustering algorithm is used to get the final clusters. Our contribution in this paper is to provide an algorithm framework for the mixed attributes clustering problem, in which existing clustering algorithms can be easily integrated, the capabilities of different kinds of clustering algorithms and characteristics of different types of datasets could be fully exploited. Comparisons with other clustering algorithms on real life datasets illustrate the superiority of our approach.
cs/0509012
Kriging Scenario For Capital Markets
cs.CE
An introduction to numerical statistics.
cs/0509013
On the variational distance of independently repeated experiments
cs.IT math.IT
Let P and Q be two probability distributions which differ only for values with non-zero probability. We show that the variational distance between the n-fold product distributions P^n and Q^n cannot grow faster than the square root of n.
cs/0509014
Density Evolution for Asymmetric Memoryless Channels
cs.IT math.IT
Density evolution is one of the most powerful analytical tools for low-density parity-check (LDPC) codes and graph codes with message passing decoding algorithms. With channel symmetry as one of its fundamental assumptions, density evolution (DE) has been widely and successfully applied to different channels, including binary erasure channels, binary symmetric channels, binary additive white Gaussian noise channels, etc. This paper generalizes density evolution for non-symmetric memoryless channels, which in turn broadens the applications to general memoryless channels, e.g. z-channels, composite white Gaussian noise channels, etc. The central theorem underpinning this generalization is the convergence to perfect projection for any fixed size supporting tree. A new iterative formula of the same complexity is then presented and the necessary theorems for the performance concentration theorems are developed. Several properties of the new density evolution method are explored, including stability results for general asymmetric memoryless channels. Simulations, code optimizations, and possible new applications suggested by this new density evolution method are also provided. This result is also used to prove the typicality of linear LDPC codes among the coset code ensemble when the minimum check node degree is sufficiently large. It is shown that the convergence to perfect projection is essential to the belief propagation algorithm even when only symmetric channels are considered. Hence the proof of the convergence to perfect projection serves also as a completion of the theory of classical density evolution for symmetric memoryless channels.
cs/0509015
Optimal Prefix Codes with Fewer Distinct Codeword Lengths are Faster to Construct
cs.DS cs.IT math.IT
A new method for constructing minimum-redundancy binary prefix codes is described. Our method does not explicitly build a Huffman tree; instead it uses a property of optimal prefix codes to compute the codeword lengths corresponding to the input weights. Let $n$ be the number of weights and $k$ be the number of distinct codeword lengths as produced by the algorithm for the optimum codes. The running time of our algorithm is $O(k \cdot n)$. Following our previous work in \cite{be}, no algorithm can possibly construct optimal prefix codes in $o(k \cdot n)$ time. When the given weights are presorted our algorithm performs $O(9^k \cdot \log^{2k}{n})$ comparisons.
cs/0509017
Traders imprint themselves by adaptively updating their own avatar
cs.MA cs.CE
Simulations of artificial stock markets were considered as early as 1964 and multi-agent ones were introduced as early as 1989. Starting the early 90's, collaborations of economists and physicists produced increasingly realistic simulation platforms. Currently, the market stylized facts are easily reproduced and one has now to address the realistic details of the Market Microstructure and of the Traders Behaviour. This calls for new methods and tools capable of bridging smoothly between simulations and experiments in economics. We propose here the following Avatar-Based Method (ABM). The subjects implement and maintain their Avatars (programs encoding their personal decision making procedures) on NatLab, a market simulation platform. Once these procedures are fed in a computer edible format, they can be operationally used as such without the need for belabouring, interpreting or conceptualising them. Thus ABM short-circuits the usual behavioural economics experiments that search for the psychological mechanisms underlying the subjects behaviour. Finally, ABM maintains a level of objectivity close to the classical behaviourism while extending its scope to subjects' decision making mechanisms. We report on experiments where Avatars designed and maintained by humans from different backgrounds (including real traders) compete in a continuous double-auction market. We hope this unbiased way of capturing the adaptive evolution of real subjects behaviour may lead to a new kind of behavioural economics experiments with a high degree of reliability, analysability and reproducibility.
cs/0509020
Transitive Text Mining for Information Extraction and Hypothesis Generation
cs.IR cs.AI
Transitive text mining - also named Swanson Linking (SL) after its primary and principal researcher - tries to establish meaningful links between literature sets which are virtually disjoint in the sense that each does not mention the main concept of the other. If successful, SL may give rise to the development of new hypotheses. In this communication we describe our approach to transitive text mining which employs co-occurrence analysis of the medical subject headings (MeSH), the descriptors assigned to papers indexed in PubMed. In addition, we will outline the current state of our web-based information system which will enable our users to perform literature-driven hypothesis building on their own.
cs/0509021
The Throughput-Reliability Tradeoff in MIMO Channels
cs.IT math.IT
In this paper, an outage limited MIMO channel is considered. We build on Zheng and Tse's elegant formulation of the diversity-multiplexing tradeoff to develop a better understanding of the asymptotic relationship between the probability of error, transmission rate, and signal-to-noise ratio. In particular, we identify the limitation imposed by the multiplexing gain notion and develop a new formulation for the throughput-reliability tradeoff that avoids this limitation. The new characterization is then used to elucidate the asymptotic trends exhibited by the outage probability curves of MIMO channels.
cs/0509022
Achievable Rates for Pattern Recognition
cs.IT cs.CV math.IT
Biological and machine pattern recognition systems face a common challenge: Given sensory data about an unknown object, classify the object by comparing the sensory data with a library of internal representations stored in memory. In many cases of interest, the number of patterns to be discriminated and the richness of the raw data force recognition systems to internally represent memory and sensory information in a compressed format. However, these representations must preserve enough information to accommodate the variability and complexity of the environment, or else recognition will be unreliable. Thus, there is an intrinsic tradeoff between the amount of resources devoted to data representation and the complexity of the environment in which a recognition system may reliably operate. In this paper we describe a general mathematical model for pattern recognition systems subject to resource constraints, and show how the aforementioned resource-complexity tradeoff can be characterized in terms of three rates related to number of bits available for representing memory and sensory data, and the number of patterns populating a given statistical environment. We prove single-letter information theoretic bounds governing the achievable rates, and illustrate the theory by analyzing the elementary cases where the pattern data is either binary or Gaussian.
cs/0509025
A formally verified proof of the prime number theorem
cs.AI cs.LO cs.SC
The prime number theorem, established by Hadamard and de la Vall'ee Poussin independently in 1896, asserts that the density of primes in the positive integers is asymptotic to 1 / ln x. Whereas their proofs made serious use of the methods of complex analysis, elementary proofs were provided by Selberg and Erd"os in 1948. We describe a formally verified version of Selberg's proof, obtained using the Isabelle proof assistant.
cs/0509028
Projecting the Forward Rate Flow onto a Finite Dimensional Manifold
cs.CE cs.IT math.IT
Given a Heath-Jarrow-Morton (HJM) interest rate model $\mathcal{M}$ and a parametrized family of finite dimensional forward rate curves $\mathcal{G}$, this paper provides a technique for projecting the infinite dimensional forward rate curve $r_{t}$ given by $\mathcal{M}$ onto the finite dimensional manifold $\mathcal{G}$.The Stratonovich dynamics of the projected finite dimensional forward curve are derived and it is shown that, under the regularity conditions, the given Stratonovich differential equation has a unique strong solution. Moreover, this projection leads to an efficient algorithm for implicit parametric estimation of the infinite dimensional HJM model. The feasibility of this method is demonstrated by applying the generalized method of moments.
cs/0509029
Quickest detection of a minimum of disorder times
cs.CE cs.IT math.IT
A multi-source quickest detection problem is considered. Assume there are two independent Poisson processes $X^{1}$ and $X^{2}$ with disorder times $\theta_{1}$ and $\theta_{2}$, respectively; that is, the intensities of $X^1$ and $X^2$ change at random unobservable times $\theta_1$ and $\theta_2$, respectively. $\theta_1$ and $\theta_2$ are independent of each other and are exponentially distributed. Define $\theta \triangleq \theta_1 \wedge \theta_2=\min\{\theta_{1},\theta_{2}\}$ . For any stopping time $\tau$ that is measurable with respect to the filtration generated by the observations define a penalty function of the form \[ R_{\tau}=\mathbb{P}(\tau<\theta)+c \mathbb{E}[(\tau-\theta)^{+}], \] where $c>0$ and $(\tau-\theta)^{+}$ is the positive part of $\tau-\theta$. It is of interest to find a stopping time $\tau$ that minimizes the above performance index. Since both observations $X^{1}$ and $X^{2}$ reveal information about the disorder time $\theta$, even this simple problem is more involved than solving the disorder problems for $X^{1}$ and $X^{2}$ separately. This problem is formulated in terms of a three dimensional sufficient statistic, and the corresponding optimal stopping problem is examined. A two dimensional optimal stopping problem whose optimal stopping time turns out to coincide with the optimal stopping time of the original problem for some range of parameters is also solved. The value function of this problem serves as a tight upper bound for the original problem's value function. The two solutions are characterized by iterating suitable functional operators.
cs/0509032
A Simple Model to Generate Hard Satisfiable Instances
cs.AI cond-mat.stat-mech cs.CC
In this paper, we try to further demonstrate that the models of random CSP instances proposed by [Xu and Li, 2000; 2003] are of theoretical and practical interest. Indeed, these models, called RB and RD, present several nice features. First, it is quite easy to generate random instances of any arity since no particular structure has to be integrated, or property enforced, in such instances. Then, the existence of an asymptotic phase transition can be guaranteed while applying a limited restriction on domain size and on constraint tightness. In that case, a threshold point can be precisely located and all instances have the guarantee to be hard at the threshold, i.e., to have an exponential tree-resolution complexity. Next, a formal analysis shows that it is possible to generate forced satisfiable instances whose hardness is similar to unforced satisfiable ones. This analysis is supported by some representative results taken from an intensive experimentation that we have carried out, using complete and incomplete search methods.
cs/0509033
K-Histograms: An Efficient Clustering Algorithm for Categorical Dataset
cs.AI
Clustering categorical data is an integral part of data mining and has attracted much attention recently. In this paper, we present k-histogram, a new efficient algorithm for clustering categorical data. The k-histogram algorithm extends the k-means algorithm to categorical domain by replacing the means of clusters with histograms, and dynamically updates histograms in the clustering process. Experimental results on real datasets show that k-histogram algorithm can produce better clustering results than k-modes algorithm, the one related with our work most closely.
cs/0509037
Friends for Free: Self-Organizing Artificial Social Networks for Trust and Cooperation
cs.MA
By harvesting friendship networks from e-mail contacts or instant message "buddy lists" Peer-to-Peer (P2P) applications can improve performance in low trust environments such as the Internet. However, natural social networks are not always suitable, reliable or available. We propose an algorithm (SLACER) that allows peer nodes to create and manage their own friendship networks. We evaluate performance using a canonical test application, requiring cooperation between peers for socially optimal outcomes. The Artificial Social Networks (ASN) produced are connected, cooperative and robust - possessing many of the disable properties of human friendship networks such as trust between friends (directly linked peers) and short paths linking everyone via a chain of friends. In addition to new application possibilities, SLACER could supply ASN to P2P applications that currently depend on human social networks thus transforming them into fully autonomous, self-managing systems.
cs/0509039
Coding for the feedback Gel'fand-Pinsker channel and the feedforward Wyner-Ziv source
cs.IT math.IT
We consider both channel coding and source coding, with perfect past feedback/feedforward, in the presence of side information. It is first observed that feedback does not increase the capacity of the Gel'fand-Pinsker channel, nor does feedforward improve the achievable rate-distortion performance in the Wyner-Ziv problem. We then focus on the Gaussian case showing that, as in the absence of side information, feedback/feedforward allows to efficiently attain the respective performance limits. In particular, we derive schemes via variations on that of Schalkwijk and Kailath. These variants, which are as simple as their origins and require no binning, are shown to achieve, respectively, the capacity of Costa's channel, and the Wyner-Ziv rate distortion function. Finally, we consider the finite-alphabet setting and derive schemes for both the channel and the source coding problems that attain the fundamental limits, using variations on schemes of Ahlswede and Ooi and Wornell, and of Martinian and Wornell, respectively.
cs/0509040
Authoring case based training by document data extraction
cs.AI cs.IR
In this paper, we propose an scalable approach to modeling based upon word processing documents, and we describe the tool Phoenix providing the technical infrastructure. For our training environment d3web.Train, we developed a tool to extract case knowledge from existing documents, usually dismissal records, extending Phoenix to d3web.CaseImporter. Independent authors used this tool to develop training systems, observing a significant decrease of time for setteling-in and a decrease of time necessary for developing a case.
cs/0509041
Efficient Reconciliation of Correlated Continuous Random Variables using LDPC Codes
cs.IT math.IT
This paper investigates an efficient and practical information reconciliation method in the case where two parties have access to correlated continuous random variables. We show that reconciliation is a special case of channel coding and that existing coded modulation techniques can be adapted for reconciliation. We describe an explicit reconciliation method based on LDPC codes in the case of correlated Gaussian variables. We believe that the proposed method can improve the efficiency of quantum key distribution protocols based on continuous-spectrum quantum states.
cs/0509043
Optimal Power Control for Multiuser CDMA Channels
cs.IT math.IT
In this paper, we define the power region as the set of power allocations for K users such that everybody meets a minimum signal-to-interference ratio (SIR). The SIR is modeled in a multiuser CDMA system with fixed linear receiver and signature sequences. We show that the power region is convex in linear and logarithmic scale. It furthermore has a componentwise minimal element. Power constraints are included by the intersection with the set of all viable power adjustments. In this framework, we aim at minimizing the total expended power by minimizing a componentwise monotone functional. If the feasible power region is nonempty, the minimum is attained. Otherwise, as a solution to balance conflicting interests, we suggest the projection of the minimum point in the power region onto the set of viable power settings. Finally, with an appropriate utility function, the problem of minimizing the total expended power can be seen as finding the Nash bargaining solution, which sheds light on power assignment from a game theoretic point of view. Convexity and componentwise monotonicity are essential prerequisites for this result.
cs/0509044
Accumulate-Repeat-Accumulate Codes: Systematic Codes Achieving the Binary Erasure Channel Capacity with Bounded Complexity
cs.IT math.IT
The paper introduces ensembles of accumulate-repeat-accumulate (ARA) codes which asymptotically achieve capacity on the binary erasure channel (BEC) with {\em bounded complexity} per information bit. It also introduces symmetry properties which play a central role in the construction of capacity-achieving ensembles for the BEC. The results here improve on the tradeoff between performance and complexity provided by the first capacity-achieving ensembles of irregular repeat-accumulate (IRA) codes with bounded complexity per information bit; these IRA ensembles were previously constructed by Pfister, Sason and Urbanke. The superiority of ARA codes with moderate to large block length is exemplified by computer simulations which compare their performance with those of previously reported capacity-achieving ensembles of LDPC and IRA codes. The ARA codes also have the advantage of being systematic.
cs/0509045
On Hats and other Covers
cs.IT math.IT
We study a game puzzle that has enjoyed recent popularity among mathematicians, computer scientist, coding theorists and even the mass press. In the game, $n$ players are fitted with randomly assigned colored hats. Individual players can see their teammates' hat colors, but not their own. Based on this information, and without any further communication, each player must attempt to guess his hat color, or pass. The team wins if there is at least one correct guess, and no incorrect ones. The goal is to devise guessing strategies that maximize the team winning probability. We show that for the case of two hat colors, and for any value of $n$, playing strategies are equivalent to binary covering codes of radius one. This link, in particular with Hamming codes, had been observed for values of $n$ of the form $2^m-1$. We extend the analysis to games with hats of $q$ colors, $q\geq 2$, where 1-coverings are not sufficient to characterize the best strategies. Instead, we introduce the more appropriate notion of a {\em strong covering}, and show efficient constructions of these coverings, which achieve winning probabilities approaching unity. Finally, we briefly discuss results on variants of the problem, including arbitrary input distributions, randomized playing strategies, and symmetric strategies.
cs/0509046
On the number of t-ary trees with a given path length
cs.DM cs.IT math.IT
We show that the number of $t$-ary trees with path length equal to $p$ is $\exp(h(t^{-1})t\log t \frac{p}{\log p}(1+o(1)))$, where $\entropy(x){=}{-}x\log x {-}(1{-}x)\log (1{-}x)$ is the binary entropy function. Besides its intrinsic combinatorial interest, the question recently arose in the context of information theory, where the number of $t$-ary trees with path length $p$ estimates the number of universal types, or, equivalently, the number of different possible Lempel-Ziv'78 dictionaries for sequences of length $p$ over an alphabet of size $t$.
cs/0509047
Secure multiplex coding to attain the channel capacity in wiretap channels
cs.IT cs.CR math.IT
It is known that a message can be transmitted safely against any wiretapper via a noisy channel without a secret key if the coding rate is less than the so-called secrecy capacity $C_S$, which is usually smaller than the channel capacity $C$. In order to remove the loss $C - C_S$, we propose a multiplex coding scheme with plural independent messages. In this paper, it is shown that the proposed multiplex coding scheme can attain the channel capacity as the total rate of the plural messages and the perfect secrecy for each message. The coding theorem is proved by extending Hayashi's proof, in which the coding of the channel resolvability is applied to wiretap channels.
cs/0509048
Capacity of Complexity-Constrained Noise-Free CDMA
cs.IT math.IT
An interference-limited noise-free CDMA downlink channel operating under a complexity constraint on the receiver is introduced. According to this paradigm, detected bits, obtained by performing hard decisions directly on the channel's matched filter output, must be the same as the transmitted binary inputs. This channel setting, allowing the use of the simplest receiver scheme, seems to be worthless, making reliable communication at any rate impossible. We prove, by adopting statistical mechanics notion, that in the large-system limit such a complexity-constrained CDMA channel gives rise to a non-trivial Shannon-theoretic capacity, rigorously analyzed and corroborated using finite-size channel simulations.
cs/0509049
On the Achievable Information Rates of CDMA Downlink with Trivial Receivers
cs.IT math.IT
A noisy CDMA downlink channel operating under a strict complexity constraint on the receiver is introduced. According to this constraint, detected bits, obtained by performing hard decisions directly on the channel's matched filter output, must be the same as the transmitted binary inputs. This channel setting, allowing the use of the simplest receiver scheme, seems to be worthless, making reliable communication at any rate impossible. However, recently this communication paradigm was shown to yield valuable information rates in the case of a noiseless channel. This finding calls for the investigation of this attractive complexity-constrained transmission scheme for the more practical noisy channel case. By adopting the statistical mechanics notion of metastable states of the renowned Hopfield model, it is proved that under a bounded noise assumption such complexity-constrained CDMA channel gives rise to a non-trivial Shannon-theoretic capacity, rigorously analyzed and corroborated using finite-size channel simulations. For unbounded noise the channel's outage capacity is addressed and specifically described for the popular additive white Gaussian noise.
cs/0509050
Effect of door delay on aircraft evacuation time
cs.MA
The recent commercial launch of twin-deck Very Large Transport Aircraft (VLTA) such as the Airbus A380 has raised questions concerning the speed at which they may be evacuated. The abnormal height of emergency exits on the upper deck has led to speculation that emotional factors such as fear may lead to door delay, and thus play a significant role in increasing overall evacuation time. Full-scale evacuation tests are financially expensive and potentially hazardous, and systematic studies of the evacuation of VLTA are rare. Here we present a computationally cheap agent-based framework for the general simulation of aircraft evacuation, and apply it to the particular case of the Airbus A380. In particular, we investigate the effect of door delay, and conclude that even a moderate average delay can lead to evacuation times that exceed the maximum for safety certification. The model suggests practical ways to minimise evacuation time, as well as providing a general framework for the simulation of evacuation.
cs/0509053
Underwater Hacker Missile Wars: A Cryptography and Engineering Contest
cs.CR cs.CE
For a recent student conference, the authors developed a day-long design problem and competition suitable for engineering, mathematics and science undergraduates. The competition included a cryptography problem, for which a workshop was run during the conference. This paper describes the competition, focusing on the cryptography problem and the workshop. Notes from the workshop and code for the computer programs are made available via the Internet. The results of a personal self-evaluation (PSE) are described.
cs/0509055
Learning Optimal Augmented Bayes Networks
cs.LG
Naive Bayes is a simple Bayesian classifier with strong independence assumptions among the attributes. This classifier, desipte its strong independence assumptions, often performs well in practice. It is believed that relaxing the independence assumptions of a naive Bayes classifier may improve the classification accuracy of the resulting structure. While finding an optimal unconstrained Bayesian Network (for most any reasonable scoring measure) is an NP-hard problem, it is possible to learn in polynomial time optimal networks obeying various structural restrictions. Several authors have examined the possibilities of adding augmenting arcs between attributes of a Naive Bayes classifier. Friedman, Geiger and Goldszmidt define the TAN structure in which the augmenting arcs form a tree on the attributes, and present a polynomial time algorithm that learns an optimal TAN with respect to MDL score. Keogh and Pazzani define Augmented Bayes Networks in which the augmenting arcs form a forest on the attributes (a collection of trees, hence a relaxation of the stuctural restriction of TAN), and present heuristic search methods for learning good, though not optimal, augmenting arc sets. The authors, however, evaluate the learned structure only in terms of observed misclassification error and not against a scoring metric, such as MDL. In this paper, we present a simple, polynomial time greedy algorithm for learning an optimal Augmented Bayes Network with respect to MDL score.
cs/0509058
Interactive Unawareness Revisited
cs.AI cs.LO
We analyze a model of interactive unawareness introduced by Heifetz, Meier and Schipper (HMS). We consider two axiomatizations for their model, which capture different notions of validity. These axiomatizations allow us to compare the HMS approach to both the standard (S5) epistemic logic and two other approaches to unawareness: that of Fagin and Halpern and that of Modica and Rustichini. We show that the differences between the HMS approach and the others are mainly due to the notion of validity used and the fact that the HMS is based on a 3-valued propositional logic.
cs/0509061
Guarantees for the Success Frequency of an Algorithm for Finding Dodgson-Election Winners
cs.DS cs.MA
In the year 1876 the mathematician Charles Dodgson, who wrote fiction under the now more famous name of Lewis Carroll, devised a beautiful voting system that has long fascinated political scientists. However, determining the winner of a Dodgson election is known to be complete for the \Theta_2^p level of the polynomial hierarchy. This implies that unless P=NP no polynomial-time solution to this problem exists, and unless the polynomial hierarchy collapses to NP the problem is not even in NP. Nonetheless, we prove that when the number of voters is much greater than the number of candidates--although the number of voters may still be polynomial in the number of candidates--a simple greedy algorithm very frequently finds the Dodgson winners in such a way that it ``knows'' that it has found them, and furthermore the algorithm never incorrectly declares a nonwinner to be a winner.
cs/0509062
Capacity-Achieving Codes with Bounded Graphical Complexity on Noisy Channels
cs.IT math.IT
We introduce a new family of concatenated codes with an outer low-density parity-check (LDPC) code and an inner low-density generator matrix (LDGM) code, and prove that these codes can achieve capacity under any memoryless binary-input output-symmetric (MBIOS) channel using maximum-likelihood (ML) decoding with bounded graphical complexity, i.e., the number of edges per information bit in their graphical representation is bounded. In particular, we also show that these codes can achieve capacity on the binary erasure channel (BEC) under belief propagation (BP) decoding with bounded decoding complexity per information bit per iteration for all erasure probabilities in (0, 1). By deriving and analyzing the average weight distribution (AWD) and the corresponding asymptotic growth rate of these codes with a rate-1 inner LDGM code, we also show that these codes achieve the Gilbert-Varshamov bound with asymptotically high probability. This result can be attributed to the presence of the inner rate-1 LDGM code, which is demonstrated to help eliminate high weight codewords in the LDPC code while maintaining a vanishingly small amount of low weight codewords.
cs/0509064
On joint coding for watermarking and encryption
cs.IT cs.CR math.IT
In continuation to earlier works where the problem of joint information embedding and lossless compression (of the composite signal) was studied in the absence \cite{MM03} and in the presence \cite{MM04} of attacks, here we consider the additional ingredient of protecting the secrecy of the watermark against an unauthorized party, which has no access to a secret key shared by the legitimate parties. In other words, we study the problem of joint coding for three objectives: information embedding, compression, and encryption.Our main result is a coding theorem that provides a single--letter characterization of the best achievable tradeoffs among the following parameters: the distortion between the composite signal and the covertext, the distortion in reconstructing the watermark by the legitimate receiver, the compressibility of the composite signal (with and without the key), and the equivocation of the watermark, as well as its reconstructed version, given the composite signal. In the attack--free case, if the key is independent of the covertext, this coding theorem gives rise to a {\it threefold} separation principle that tells that asymptotically, for long block codes, no optimality is lost by first applying a rate--distortion code to the watermark source, then encrypting the compressed codeword, and finally, embedding it into the covertext using the embedding scheme of \cite{MM03}. In the more general case, however, this separation principle is no longer valid, as the key plays an additional role of side information used by the embedding unit.
cs/0509065
On Deciding Deep Holes of Reed-Solomon Codes
cs.IT math.IT
For generalized Reed-Solomon codes, it has been proved \cite{GuruswamiVa05} that the problem of determining if a received word is a deep hole is co-NP-complete. The reduction relies on the fact that the evaluation set of the code can be exponential in the length of the code -- a property that practical codes do not usually possess. In this paper, we first presented a much simpler proof of the same result. We then consider the problem for standard Reed-Solomon codes, i.e. the evaluation set consists of all the nonzero elements in the field. We reduce the problem of identifying deep holes to deciding whether an absolutely irreducible hypersurface over a finite field contains a rational point whose coordinates are pairwise distinct and nonzero. By applying Schmidt and Cafure-Matera estimation of rational points on algebraic varieties, we prove that the received vector $(f(\alpha))_{\alpha \in \F_q}$ for Reed-Solomon $[q,k]_q$, $k < q^{1/7 - \epsilon}$, cannot be a deep hole, whenever $f(x)$ is a polynomial of degree $k+d$ for $1\leq d < q^{3/13 -\epsilon}$.
cs/0509068
Channel Uncertainty in Ultra Wideband Communication Systems
cs.IT math.IT
Wide band systems operating over multipath channels may spread their power over bandwidth if they use duty cycle. Channel uncertainty limits the achievable data rates of power constrained wide band systems; Duty cycle transmission reduces the channel uncertainty because the receiver has to estimate the channel only when transmission takes place. The optimal choice of the fraction of time used for transmission depends on the spectral efficiency of the signal modulation. The general principle is demonstrated by comparing the channel conditions that allow different modulations to achieve the capacity in the limit. Direct sequence spread spectrum and pulse position modulation systems with duty cycle achieve the channel capacity, if the increase of the number of channel paths with the bandwidth is not too rapid. The higher spectral efficiency of the spread spectrum modulation lets it achieve the channel capacity in the limit, in environments where pulse position modulation with non-vanishing symbol time cannot be used because of the large number of channel paths.
cs/0509071
CP-nets and Nash equilibria
cs.GT cs.AI
We relate here two formalisms that are used for different purposes in reasoning about multi-agent systems. One of them are strategic games that are used to capture the idea that agents interact with each other while pursuing their own interest. The other are CP-nets that were introduced to express qualitative and conditional preferences of the users and which aim at facilitating the process of preference elicitation. To relate these two formalisms we introduce a natural, qualitative, extension of the notion of a strategic game. We show then that the optimal outcomes of a CP-net are exactly the Nash equilibria of an appropriately defined strategic game in the above sense. This allows us to use the techniques of game theory to search for optimal outcomes of CP-nets and vice-versa, to use techniques developed for CP-nets to search for Nash equilibria of the considered games.
cs/0509072
Folksonomy as a Complex Network
cs.IR cs.DL physics.soc-ph
Folksonomy is an emerging technology that works to classify the information over WWW through tagging the bookmarks, photos or other web-based contents. It is understood to be organized by every user while not limited to the authors of the contents and the professional editors. This study surveyed the folksonomy as a complex network. The result indicates that the network, which is composed of the tags from the folksonomy, displays both properties of small world and scale-free. However, the statistics only shows a local and static slice of the vast body of folksonomy which is still evolving.
cs/0509073
Distance-Increasing Maps of All Length by Simple Mapping Algorithms
cs.IT cs.DM math.IT
Distance-increasing maps from binary vectors to permutations, namely DIMs, are useful for the construction of permutation arrays. While a simple mapping algorithm defining DIMs of even length is known, existing DIMs of odd length are either recursively constructed by merging shorter DIMs or defined by much complicated mapping algorithms. In this paper, DIMs of all length defined by simple mapping algorithms are presented.
cs/0509075
On the Capacity of Doubly Correlated MIMO Channels
cs.IT math.IT
In this paper, we analyze the capacity of multiple-input multiple-output (MIMO) Rayleigh-fading channels in the presence of spatial fading correlation at both the transmitter and the receiver, assuming that the channel is unknown at the transmitter and perfectly known at the receiver. We first derive the determinant representation for the exact characteristic function of the capacity, which is then used to determine the trace representations for the mean, variance, skewness, kurtosis, and other higher-order statistics (HOS). These results allow us to exactly evaluate two relevant information-theoretic capacity measures--ergodic capacity and outage capacity--and the HOS of the capacity for such a MIMO channel. The analytical framework presented in the paper is valid for arbitrary numbers of antennas and generalizes the previously known results for independent and identically distributed or one-sided correlated MIMO channels to the case when fading correlation exists on both sides. We verify our analytical results by comparing them with Monte Carlo simulations for a correlation model based on realistic channel measurements as well as a classical exponential correlation model.
cs/0509077
Capacity Limits of Cognitive Radio with Distributed and Dynamic Spectral Activity
cs.IT math.IT
We investigate the capacity of opportunistic communication in the presence of dynamic and distributed spectral activity, i.e. when the time varying spectral holes sensed by the cognitive transmitter are correlated but not identical to those sensed by the cognitive receiver. Using the information theoretic framework of communication with causal and non-causal side information at the transmitter and/or the receiver, we obtain analytical capacity expressions and the corresponding numerical results. We find that cognitive radio communication is robust to dynamic spectral environments even when the communication occurs in bursts of only 3-5 symbols. The value of handshake overhead is investigated for both lightly loaded and heavily loaded systems. We find that the capacity benefits of overhead information flow from the transmitter to the receiver is negligible while feedback information overhead in the opposite direction significantly improves capacity.
cs/0509078
On the Feedback Capacity of Stationary Gaussian Channels
cs.IT math.IT
The capacity of stationary additive Gaussian noise channels with feedback is characterized as the solution to a variational problem. Toward this end, it is proved that the optimal feedback coding scheme is stationary. When specialized to the first-order autoregressive moving-average noise spectrum, this variational characterization yields a closed-form expression for the feedback capacity. In particular, this result shows that the celebrated Schalkwijk--Kailath coding scheme achieves the feedback capacity for the first-order autoregressive moving-average Gaussian channel, resolving a long-standing open problem studied by Butman, Schalkwijk--Tiernan, Wolfowitz, Ozarow, Ordentlich, Yang--Kavcic--Tatikonda, and others.
cs/0509079
The WSSUS Pulse Design Problem in Multicarrier Transmission
cs.IT math.IT
Optimal link adaption to the scattering function of wide sense stationary uncorrelated mobile communication channels is still an unsolved problem despite its importance for next-generation system design. In multicarrier transmission such link adaption is performed by pulse shaping, i.e. by properly adjusting the transmit and receive filters. For example pulse shaped Offset--QAM systems have been recently shown to have superior performance over standard cyclic prefix OFDM (while operating at higher spectral efficiency).In this paper we establish a general mathematical framework for joint transmitter and receiver pulse shape optimization for so-called Weyl--Heisenberg or Gabor signaling with respect to the scattering function of the WSSUS channel. In our framework the pulse shape optimization problem is translated to an optimization problem over trace class operators which in turn is related to fidelity optimization in quantum information processing. By convexity relaxation the problem is shown to be equivalent to a \emph{convex constraint quasi-convex maximization problem} thereby revealing the non-convex nature of the overall WSSUS pulse design problem. We present several iterative algorithms for optimization providing applicable results even for large--scale problem constellations. We show that with transmitter-side knowledge of the channel statistics a gain of $3 - 6$dB in $\SINR$ can be expected.
cs/0509080
Capacity and Character Expansions: Moment generating function and other exact results for MIMO correlated channels
cs.IT cond-mat.mes-hall cond-mat.stat-mech hep-lat math-ph math.IT math.MP
We apply a promising new method from the field of representations of Lie groups to calculate integrals over unitary groups, which are important for multi-antenna communications. To demonstrate the power and simplicity of this technique, we first re-derive a number of results that have been used recently in the community of wireless information theory, using only a few simple steps. In particular, we derive the joint probability distribution of eigenvalues of the matrix GG*, with G a semicorrelated Gaussian random matrix or a Gaussian random matrix with a non-zero mean (and G* its hermitian conjugate) . These joint probability distribution functions can then be used to calculate the moment generating function of the mutual information for Gaussian channels with multiple antennas on both ends with this probability distribution of their channel matrices G. We then turn to the previously unsolved problem of calculating the moment generating function of the mutual information of MIMO (multiple input-multiple output) channels, which are correlated at both the receiver and the transmitter. From this moment generating function we obtain the ergodic average of the mutual information and study the outage probability. These methods can be applied to a number of other problems. As a particular example, we examine unitary encoded space-time transmission of MIMO systems and we derive the received signal distribution when the channel matrix is correlated at the transmitter end.
cs/0509081
Automatic Face Recognition System Based on Local Fourier-Bessel Features
cs.CV
We present an automatic face verification system inspired by known properties of biological systems. In the proposed algorithm the whole image is converted from the spatial to polar frequency domain by a Fourier-Bessel Transform (FBT). Using the whole image is compared to the case where only face image regions (local analysis) are considered. The resulting representations are embedded in a dissimilarity space, where each image is represented by its distance to all the other images, and a Pseudo-Fisher discriminator is built. Verification test results on the FERET database showed that the local-based algorithm outperforms the global-FBT version. The local-FBT algorithm performed as state-of-the-art methods under different testing conditions, indicating that the proposed system is highly robust for expression, age, and illumination variations. We also evaluated the performance of the proposed system under strong occlusion conditions and found that it is highly robust for up to 50% of face occlusion. Finally, we automated completely the verification system by implementing face and eye detection algorithms. Under this condition, the local approach was only slightly superior to the global approach.
cs/0509082
Face Recognition Based on Polar Frequency Features
cs.CV
A novel biologically motivated face recognition algorithm based on polar frequency is presented. Polar frequency descriptors are extracted from face images by Fourier-Bessel transform (FBT). Next, the Euclidean distance between all images is computed and each image is now represented by its dissimilarity to the other images. A Pseudo-Fisher Linear Discriminant was built on this dissimilarity space. The performance of Discrete Fourier transform (DFT) descriptors, and a combination of both feature types was also evaluated. The algorithms were tested on a 40- and 1196-subjects face database (ORL and FERET, respectively). With 5 images per subject in the training and test datasets, error rate on the ORL database was 3.8, 1.25 and 0.2% for the FBT, DFT, and the combined classifier, respectively, as compared to 2.6% achieved by the best previous algorithm. The most informative polar frequency features were concentrated at low-to-medium angular frequencies coupled to low radial frequencies. On the FERET database, where an affine normalization pre-processing was applied, the FBT algorithm outperformed only the PCA in a rank recognition test. However, it achieved performance comparable to state-of-the-art methods when evaluated by verification tests. These results indicate the high informative value of the polar frequency content of face images in relation to recognition and verification tasks, and that the Cartesian frequency content can complement information about the subjects' identity, but possibly only when the images are not pre-normalized. Possible implications for human face recognition are discussed.
cs/0509083
Face Verification in Polar Frequency Domain: a Biologically Motivated Approach
cs.CV
We present a novel local-based face verification system whose components are analogous to those of biological systems. In the proposed system, after global registration and normalization, three eye regions are converted from the spatial to polar frequency domain by a Fourier-Bessel Transform. The resulting representations are embedded in a dissimilarity space, where each image is represented by its distance to all the other images. In this dissimilarity space a Pseudo-Fisher discriminator is built. ROC and equal error rate verification test results on the FERET database showed that the system performed at least as state-of-the-art methods and better than a system based on polar Fourier features. The local-based system is especially robust to facial expression and age variations, but sensitive to registration errors.
cs/0509085
An Improved Lower Bound to the Number of Neighbors Required for the Asymptotic Connectivity of Ad Hoc Networks
cs.NI cs.IT math.IT
Xue and Kumar have established that the number of neighbors required for connectivity of wireless networks with N uniformly distributed nodes must grow as log(N), and they also established that the actual number required lies between 0.074log(N) and 5.1774log(N). In this short paper, by recognizing that connectivity results for networks where the nodes are distributed according to a Poisson point process can often be applied to the problem for a network with N nodes, we are able to improve the lower bound. In particular, we show that a network with nodes distributed in a unit square according to a 2D Poisson point process of parameter N will be asymptotically disconnected with probability one if the number of neighbors is less than 0.129log(N). Moreover, similar number of neighbors is not enough for an asymptotically connected network with N nodes uniformly in a unit square, hence improving the lower bound.
cs/0509086
Statistical Mechanical Approach to Lossy Data Compression:Theory and Practice
cs.IT math.IT
The encoder and decoder for lossy data compression of binary memoryless sources are developed on the basis of a specific-type nonmonotonic perceptron. Statistical mechanical analysis indicates that the potential ability of the perceptron-based code saturates the theoretically achievable limit in most cases although exactly performing the compression is computationally difficult. To resolve this difficulty, we provide a computationally tractable approximation algorithm using belief propagation (BP), which is a current standard algorithm of probabilistic inference. Introducing several approximations and heuristics, the BP-based algorithm exhibits performance that is close to the achievable limit in a practical time scale in optimal cases.
cs/0509087
On Time-Variant Distortions in Multicarrier Transmission with Application to Frequency Offsets and Phase Noise
cs.IT math.IT
Phase noise and frequency offsets are due to their time-variant behavior one of the most limiting disturbances in practical OFDM designs and therefore intensively studied by many authors. In this paper we present a generalized framework for the prediction of uncoded system performance in the presence of time-variant distortions including the transmitter and receiver pulse shapes as well as the channel. Therefore, unlike existing studies, our approach can be employed for more general multicarrier schemes. To show the usefulness of our approach, we apply the results to OFDM in the context of frequency offset and Wiener phase noise, yielding improved bounds on the uncoded performance. In particular, we obtain exact formulas for the averaged performance in AWGN and time-invariant multipath channels.
cs/0509088
Business intelligence systems and user's parameters: an application to a documents' database
cs.DB
This article presents earlier results of our research works in the area of modeling Business Intelligence Systems. The basic idea of this research area is presented first. We then show the necessity of including certain users' parameters in Information systems that are used in Business Intelligence systems in order to integrate a better response from such systems. We identified two main types of attributes that can be missing from a base and we showed why they needed to be included. A user model that is based on a cognitive user evolution is presented. This model when used together with a good definition of the information needs of the user (decision maker) will accelerate his decision making process.
cs/0509089
Semantics of UML 2.0 Activity Diagram for Business Modeling by Means of Virtual Machine
cs.CE cs.PL
The paper proposes a more formalized definition of UML 2.0 Activity Diagram semantics. A subset of activity diagram constructs relevant for business process modeling is considered. The semantics definition is based on the original token flow methodology, but a more constructive approach is used. The Activity Diagram Virtual machine is defined by means of a metamodel, with operations defined by a mix of pseudocode and OCL pre- and postconditions. A formal procedure is described which builds the virtual machine for any activity diagram. The relatively complicated original token movement rules in control nodes and edges are combined into paths from an action to action. A new approach is the use of different (push and pull) engines, which move tokens along the paths. Pull engines are used for paths containing join nodes, where the movement of several tokens must be coordinated. The proposed virtual machine approach makes the activity semantics definition more transparent where the token movement can be easily traced. However, the main benefit of the approach is the possibility to use the defined virtual machine as a basis for UML activity diagram based workflow or simulation engine.
cs/0509092
Automatic extraction of paraphrastic phrases from medium size corpora
cs.CL cs.AI
This paper presents a versatile system intended to acquire paraphrastic phrases from a representative corpus. In order to decrease the time spent on the elaboration of resources for NLP system (for example Information Extraction, IE hereafter), we suggest to use a machine learning system that helps defining new templates and associated resources. This knowledge is automatically derived from the text collection, in interaction with a large semantic network.
cs/0509093
On the Outage Capacity of Correlated Multiple-Path MIMO Channels
cs.IT math.IT
The use of multi-antenna arrays in both transmission and reception has been shown to dramatically increase the throughput of wireless communication systems. As a result there has been considerable interest in characterizing the ergodic average of the mutual information for realistic correlated channels. Here, an approach is presented that provides analytic expressions not only for the average, but also the higher cumulant moments of the distribution of the mutual information for zero-mean Gaussian (multiple-input multiple-output) MIMO channels with the most general multipath covariance matrices when the channel is known at the receiver. These channels include multi-tap delay paths, as well as general channels with covariance matrices that cannot be written as a Kronecker product, such as dual-polarized antenna arrays with general correlations at both transmitter and receiver ends. The mathematical methods are formally valid for large antenna numbers, in which limit it is shown that all higher cumulant moments of the distribution, other than the first two scale to zero. Thus, it is confirmed that the distribution of the mutual information tends to a Gaussian, which enables one to calculate the outage capacity. These results are quite accurate even in the case of a few antennas, which makes this approach applicable to realistic situations.
cs/0509096
Performance Analysis and Enhancement of Multiband OFDM for UWB Communications
cs.IT math.IT
In this paper, we analyze the frequency-hopping orthogonal frequency-division multiplexing (OFDM) system known as Multiband OFDM for high-rate wireless personal area networks (WPANs) based on ultra-wideband (UWB) transmission. Besides considering the standard, we also propose and study system performance enhancements through the application of Turbo and Repeat-Accumulate (RA) codes, as well as OFDM bit-loading. Our methodology consists of (a) a study of the channel model developed under IEEE 802.15 for UWB from a frequency-domain perspective suited for OFDM transmission, (b) development and quantification of appropriate information-theoretic performance measures, (c) comparison of these measures with simulation results for the Multiband OFDM standard proposal as well as our proposed extensions, and (d) the consideration of the influence of practical, imperfect channel estimation on the performance. We find that the current Multiband OFDM standard sufficiently exploits the frequency selectivity of the UWB channel, and that the system performs in the vicinity of the channel cutoff rate. Turbo codes and a reduced-complexity clustered bit-loading algorithm improve the system power efficiency by over 6 dB at a data rate of 480 Mbps.
cs/0509097
Iterative Algebraic Soft-Decision List Decoding of Reed-Solomon Codes
cs.IT math.IT
In this paper, we present an iterative soft-decision decoding algorithm for Reed-Solomon codes offering both complexity and performance advantages over previously known decoding algorithms. Our algorithm is a list decoding algorithm which combines two powerful soft decision decoding techniques which were previously regarded in the literature as competitive, namely, the Koetter-Vardy algebraic soft-decision decoding algorithm and belief-propagation based on adaptive parity check matrices, recently proposed by Jiang and Narayanan. Building on the Jiang-Narayanan algorithm, we present a belief-propagation based algorithm with a significant reduction in computational complexity. We introduce the concept of using a belief-propagation based decoder to enhance the soft-input information prior to decoding with an algebraic soft-decision decoder. Our algorithm can also be viewed as an interpolation multiplicity assignment scheme for algebraic soft-decision decoding of Reed-Solomon codes.
cs/0509098
Applications of correlation inequalities to low density graphical codes
cs.IT cond-mat.stat-mech math.IT
This contribution is based on the contents of a talk delivered at the Next-SigmaPhi conference held in Crete in August 2005. It is adressed to an audience of physicists with diverse horizons and does not assume any background in communications theory. Capacity approaching error correcting codes for channel communication known as Low Density Parity Check (LDPC) codes have attracted considerable attention from coding theorists in the last decade. Surprisingly strong connections with the theory of diluted spin glasses have been discovered. In this work we elucidate one new connection, namely that a class of correlation inequalities valid for gaussian spin glasses can be applied to the theoretical analysis of LDPC codes. This allows for a rigorous comparison between the so called (optimal) maximum a posteriori and the computationaly efficient belief propagation decoders. The main ideas of the proofs are explained and we refer to recent works for the more lengthy technical details.
cs/0510001
Retinal Vessel Segmentation Using the 2-D Morlet Wavelet and Supervised Classification
cs.CV
We present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or non-vessel, based on the pixel's feature vector. Feature vectors are composed of the pixel's intensity and continuous two-dimensional Morlet wavelet transform responses taken at multiple scales. The Morlet wavelet is capable of tuning to specific frequencies, thus allowing noise filtering and vessel enhancement in a single step. We use a Bayesian classifier with class-conditional probability density functions (likelihoods) described as Gaussian mixtures, yielding a fast classification, while being able to model complex decision surfaces and compare its performance with the linear minimum squared error classifier. The probability distributions are estimated based on a training set of labeled pixels obtained from manual segmentations. The method's performance is evaluated on publicly available DRIVE and STARE databases of manually labeled non-mydriatic images. On the DRIVE database, it achieves an area under the receiver operating characteristic (ROC) curve of 0.9598, being slightly superior than that presented by the method of Staal et al.
cs/0510002
Optimal Relay Functionality for SNR Maximization in Memoryless Relay Networks
cs.IT math.IT
We explore the SNR-optimal relay functionality in a \emph{memoryless} relay network, i.e. a network where, during each channel use, the signal transmitted by a relay depends only on the last received symbol at that relay. We develop a generalized notion of SNR for the class of memoryless relay functions. The solution to the generalized SNR optimization problem leads to the novel concept of minimum mean square uncorrelated error estimation(MMSUEE). For the elemental case of a single relay, we show that MMSUEE is the SNR-optimal memoryless relay function regardless of the source and relay transmit power, and the modulation scheme. This scheme, that we call estimate and forward (EF), is also shown to be SNR-optimal with PSK modulation in a parallel relay network. We demonstrate that EF performs better than the best of amplify and forward (AF) and demodulate and forward (DF), in both parallel and serial relay networks. We also determine that AF is near-optimal at low transmit power in a parallel network, while DF is near-optimal at high transmit power in a serial network. For hybrid networks that contain both serial and parallel elements, and when robust performance is desired, the advantage of EF over the best of AF and DF is found to be significant. Error probabilities are provided to substantiate the performance gain obtained through SNR optimality. We also show that, for \emph{Gaussian} inputs, AF, DF and EF become identical.
cs/0510003
Generalized ABBA Space-Time Block Codes
cs.IT math.IT
Linear space-time block codes (STBCs) of unitary rate and full diversity, systematically constructed over arbitrary constellations for any number of transmit antennas are introduced. The codes are obtained by generalizing the existing ABBA STBCs, a.k.a quasi-orthogonal STBCs (QO-STBCs). Furthermore, a fully orthogonal (symbol-by-symbol) decoder for the new generalized ABBA (GABBA) codes is provided. This remarkably low-complexity decoder relies on partition orthogonality properties of the code structure to decompose the received signal vector into lower-dimension tuples, each dependent only on certain subsets of the transmitted symbols. Orthogonal decodability results from the nested application of this technique, with no matrix inversion or iterative signal processing required. The exact bit-error-rate probability of GABBA codes over generalized fading channels with maximum likelihood (ML) decoding is evaluated analytically and compared against simulation results obtained with the proposed orthogonal decoder. The comparison reveals that the proposed GABBA solution, despite its very low complexity, achieves nearly the same performance of the bound corresponding to the ML-decoded system, especially in systems with large numbers of antennas.
cs/0510005
Taylor series expansions for the entropy rate of Hidden Markov Processes
cs.IT cond-mat.stat-mech math.IT
Finding the entropy rate of Hidden Markov Processes is an active research topic, of both theoretical and practical importance. A recently used approach is studying the asymptotic behavior of the entropy rate in various regimes. In this paper we generalize and prove a previous conjecture relating the entropy rate to entropies of finite systems. Building on our new theorems, we establish series expansions for the entropy rate in two different regimes. We also study the radius of convergence of the two series expansions.
cs/0510008
Accurate and robust image superresolution by neural processing of local image representations
cs.CV cs.NE
Image superresolution involves the processing of an image sequence to generate a still image with higher resolution. Classical approaches, such as bayesian MAP methods, require iterative minimization procedures, with high computational costs. Recently, the authors proposed a method to tackle this problem, based on the use of a hybrid MLP-PNN architecture. In this paper, we present a novel superresolution method, based on an evolution of this concept, to incorporate the use of local image models. A neural processing stage receives as input the value of model coefficients on local windows. The data dimensionality is firstly reduced by application of PCA. An MLP, trained on synthetic sequences with various amounts of noise, estimates the high-resolution image data. The effect of varying the dimension of the network input space is examined, showing a complex, structured behavior. Quantitative results are presented showing the accuracy and robustness of the proposed method.
cs/0510009
Tree-Based Construction of LDPC Codes Having Good Pseudocodeword Weights
cs.IT math.IT
We present a tree-based construction of LDPC codes that have minimum pseudocodeword weight equal to or almost equal to the minimum distance, and perform well with iterative decoding. The construction involves enumerating a $d$-regular tree for a fixed number of layers and employing a connection algorithm based on permutations or mutually orthogonal Latin squares to close the tree. Methods are presented for degrees $d=p^s$ and $d = p^s+1$, for $p$ a prime. One class corresponds to the well-known finite-geometry and finite generalized quadrangle LDPC codes; the other codes presented are new. We also present some bounds on pseudocodeword weight for $p$-ary LDPC codes. Treating these codes as $p$-ary LDPC codes rather than binary LDPC codes improves their rates, minimum distances, and pseudocodeword weights, thereby giving a new importance to the finite geometry LDPC codes where $p > 2$.
cs/0510013
Safe Data Sharing and Data Dissemination on Smart Devices
cs.CR cs.DB
The erosion of trust put in traditional database servers, the growing interest for different forms of data dissemination and the concern for protecting children from suspicious Internet content are different factors that lead to move the access control from servers to clients. Several encryption schemes can be used to serve this purpose but all suffer from a static way of sharing data. In a precedent paper, we devised smarter client-based access control managers exploiting hardware security elements on client devices. The goal pursued is being able to evaluate dynamic and personalized access control rules on a ciphered XML input document, with the benefit of dissociating access rights from encryption. In this demonstration, we validate our solution using a real smart card platform and explain how we deal with the constraints usually met on hardware security elements (small memory and low throughput). Finally, we illustrate the generality of the approach and the easiness of its deployment through two different applications: a collaborative application and a parental control application on video streams.