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cs/0609076
Asymptotic Spectral Distribution of Crosscorrelation Matrix in Asynchronous CDMA
cs.IT math.IT
Asymptotic spectral distribution (ASD) of the crosscorrelation matrix is investigated for a random spreading short/long-code asynchronous direct sequence-code division multiple access (DS-CDMA) system. The discrete-time decision statistics are obtained as the output samples of a bank of symbol matched filters of all users. The crosscorrelation matrix is studied when the number of symbols transmitted by each user tends to infinity. Two levels of asynchronism are considered. One is symbol-asynchronous but chip-synchronous, and the other is chip-asynchronous. The existence of a nonrandom ASD is proved by moment convergence theorem, where the focus is on the derivation of asymptotic eigenvalue moments (AEM) of the crosscorrelation matrix. A combinatorics approach based on noncrossing partition of set partition theory is adopted for AEM computation. The spectral efficiency and the minimum mean-square-error (MMSE) achievable by a linear receiver of asynchronous CDMA are plotted by AEM using a numerical method.
cs/0609079
Modern Statistics by Kriging
cs.NA cs.CE
We present statistics (S-statistics) based only on random variable (not random value) with a mean squared error of mean estimation as a concept of error.
cs/0609081
Recurrence relations and fast algorithms
cs.CE cs.NA
We construct fast algorithms for evaluating transforms associated with families of functions which satisfy recurrence relations. These include algorithms both for computing the coefficients in linear combinations of the functions, given the values of these linear combinations at certain points, and, vice versa, for evaluating such linear combinations at those points, given the coefficients in the linear combinations; such procedures are also known as analysis and synthesis of series of certain special functions. The algorithms of the present paper are efficient in the sense that their computational costs are proportional to n (ln n) (ln(1/epsilon))^3, where n is the amount of input and output data, and epsilon is the precision of computations. Stated somewhat more precisely, we find a positive real number C such that, for any positive integer n > 10, the algorithms require at most C n (ln n) (ln(1/epsilon))^3 floating-point operations and words of memory to evaluate at n appropriately chosen points any linear combination of n special functions, given the coefficients in the linear combination, where epsilon is the precision of computations.
cs/0609087
A comparative analysis of the geometrical surface texture of a real and virtual model of a tooth flank of a cylindrical gear
cs.CE
The paper presents the methodology of modelling tooth flanks of cylindrical gears in the Cad environment. The modelling consists in a computer simulation of gear generation. A model of tooth flanks is an envelope curve of a family of envelopes that originate from the rolling motion of a solid tool model in relation to a solid model of the cylindrical gear. The surface stereometry and topography of the tooth flanks, hobbed and chiselled by Fellows method, are compared to their numerical models. Metrological measurements of the real gears were carried out using a coordinated measuring machine and a two - and a three-dimensional profilometer. A computer simulation of the gear generation was performed in the Mechanical Desktop environment.
cs/0609088
Deriving the Normalized Min-Sum Algorithm from Cooperative Optimization
cs.IT math.IT
The normalized min-sum algorithm can achieve near-optimal performance at decoding LDPC codes. However, it is a critical question to understand the mathematical principle underlying the algorithm. Traditionally, people thought that the normalized min-sum algorithm is a good approximation to the sum-product algorithm, the best known algorithm for decoding LDPC codes and Turbo codes. This paper offers an alternative approach to understand the normalized min-sum algorithm. The algorithm is derived directly from cooperative optimization, a newly discovered general method for global/combinatorial optimization. This approach provides us another theoretical basis for the algorithm and offers new insights on its power and limitation. It also gives us a general framework for designing new decoding algorithms.
cs/0609089
Fast Min-Sum Algorithms for Decoding of LDPC over GF(q)
cs.IT math.IT
In this paper, we present a fast min-sum algorithm for decoding LDPC codes over GF(q). Our algorithm is different from the one presented by David Declercq and Marc Fossorier in ISIT 05 only at the way of speeding up the horizontal scan in the min-sum algorithm. The Declercq and Fossorier's algorithm speeds up the computation by reducing the number of configurations, while our algorithm uses the dynamic programming instead. Compared with the configuration reduction algorithm, the dynamic programming one is simpler at the design stage because it has less parameters to tune. Furthermore, it does not have the performance degradation problem caused by the configuration reduction because it searches the whole configuration space efficiently through dynamic programming. Both algorithms have the same level of complexity and use simple operations which are suitable for hardware implementations.
cs/0609090
Single-Scan Min-Sum Algorithms for Fast Decoding of LDPC Codes
cs.IT math.IT
Many implementations for decoding LDPC codes are based on the (normalized/offset) min-sum algorithm due to its satisfactory performance and simplicity in operations. Usually, each iteration of the min-sum algorithm contains two scans, the horizontal scan and the vertical scan. This paper presents a single-scan version of the min-sum algorithm to speed up the decoding process. It can also reduce memory usage or wiring because it only needs the addressing from check nodes to variable nodes while the original min-sum algorithm requires that addressing plus the addressing from variable nodes to check nodes. To cut down memory usage or wiring further, another version of the single-scan min-sum algorithm is presented where the messages of the algorithm are represented by single bit values instead of using fixed point ones. The software implementation has shown that the single-scan min-sum algorithm is more than twice as fast as the original min-sum algorithm.
cs/0609093
PAC Learning Mixtures of Axis-Aligned Gaussians with No Separation Assumption
cs.LG
We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kearns et al. Here the task is to construct a hypothesis mixture of Gaussians that is statistically indistinguishable from the actual mixture generating the data; specifically, the KL-divergence should be at most epsilon. In this scenario, we give a poly(n/epsilon)-time algorithm that learns the class of mixtures of any constant number of axis-aligned Gaussians in n-dimensional Euclidean space. Our algorithm makes no assumptions about the separation between the means of the Gaussians, nor does it have any dependence on the minimum mixing weight. This is in contrast to learning results known in the ``clustering'' model, where such assumptions are unavoidable. Our algorithm relies on the method of moments, and a subalgorithm developed in previous work by the authors (FOCS 2005) for a discrete mixture-learning problem.
cs/0609094
An Improved Sphere-Packing Bound Targeting Codes of Short to Moderate Block Lengths and Applications
cs.IT math.IT
This paper derives an improved sphere-packing (ISP) bound targeting codes of short to moderate block lengths. We first review the 1967 sphere-packing (SP67) bound for discrete memoryless channels, and a recent improvement by Valembois and Fossorier. These concepts are used for the derivation of a new lower bound on the decoding error probability (referred to as the ISP bound) which is uniformly tighter than the SP67 bound and its recent improved version. Under a mild condition, the ISP bound is applicable to general memoryless channels, and some of its applications are exemplified. Its tightness is studied by comparing it with bounds on the ML decoding error probability. It is exemplified that the ISP bound suggests an interesting alternative to the 1959 sphere-packing (SP59) bound of Shannon for the Gaussian channel, especially for digital modulations of high spectral efficiency.
cs/0609096
Finite-State Dimension and Lossy Decompressors
cs.CC cs.IT math.IT
This paper examines information-theoretic questions regarding the difficulty of compressing data versus the difficulty of decompressing data and the role that information loss plays in this interaction. Finite-state compression and decompression are shown to be of equivalent difficulty, even when the decompressors are allowed to be lossy. Inspired by Kolmogorov complexity, this paper defines the optimal *decompression *ratio achievable on an infinite sequence by finite-state decompressors (that is, finite-state transducers outputting the sequence in question). It is shown that the optimal compression ratio achievable on a sequence S by any *information lossless* finite state compressor, known as the finite-state dimension of S, is equal to the optimal decompression ratio achievable on S by any finite-state decompressor. This result implies a new decompression characterization of finite-state dimension in terms of lossy finite-state transducers.
cs/0609097
Traveing Salesperson Problems for a double integrator
cs.RO
In this paper we propose some novel path planning strategies for a double integrator with bounded velocity and bounded control inputs. First, we study the following version of the Traveling Salesperson Problem (TSP): given a set of points in $\real^d$, find the fastest tour over the point set for a double integrator. We first give asymptotic bounds on the time taken to complete such a tour in the worst-case. Then, we study a stochastic version of the TSP for double integrator where the points are randomly sampled from a uniform distribution in a compact environment in $\real^2$ and $\real^3$. We propose novel algorithms that perform within a constant factor of the optimal strategy with high probability. Lastly, we study a dynamic TSP: given a stochastic process that generates targets, is there a policy which guarantees that the number of unvisited targets does not diverge over time? If such stable policies exist, what is the minimum wait for a target? We propose novel stabilizing receding-horizon algorithms whose performances are within a constant factor from the optimum with high probability, in $\real^2$ as well as $\real^3$. We also argue that these algorithms give identical performances for a particular nonholonomic vehicle, Dubins vehicle.
cs/0609099
Coding for Parallel Channels: Gallager Bounds and Applications to Repeat-Accumulate Codes
cs.IT math.IT
This paper is focused on the performance analysis of binary linear block codes (or ensembles) whose transmission takes place over independent and memoryless parallel channels. New upper bounds on the maximum-likelihood (ML) decoding error probability are derived. The framework of the second version of the Duman and Salehi (DS2) bounds is generalized to the case of parallel channels, along with the derivation of optimized tilting measures. The connection between the generalized DS2 and the 1961 Gallager bounds, known previously for a single channel, is revisited for the case of parallel channels. The new bounds are used to obtain improved inner bounds on the attainable channel regions under ML decoding. These improved bounds are applied to ensembles of turbo-like codes, focusing on repeat-accumulate codes and their recent variations.
cs/0609100
Total Variation Minimization and Graph Cuts for Moving Objects Segmentation
cs.CV
In this paper, we are interested in the application to video segmentation of the discrete shape optimization problem involving the shape weighted perimeter and an additional term depending on a parameter. Based on recent works and in particular the one of Darbon and Sigelle, we justify the equivalence of the shape optimization problem and a weighted total variation regularization. For solving this problem, we adapt the projection algorithm proposed recently for solving the basic TV regularization problem. Another solution to the shape optimization investigated here is the graph cut technique. Both methods have the advantage to lead to a global minimum. Since we can distinguish moving objects from static elements of a scene by analyzing norm of the optical flow vectors, we choose the optical flow norm as initial data. In order to have the contour as close as possible to an edge in the image, we use a classical edge detector function as the weight of the weighted total variation. This model has been used in one of our former works. We also apply the same methods to a video segmentation model used by Jehan-Besson, Barlaud and Aubert. In this case, only standard perimeter is incorporated in the shape functional. We also propose another way for finding moving objects by using an a contrario detection of objects on the image obtained by solving the Rudin-Osher-Fatemi Total Variation regularization problem.We can notice the segmentation can be associated to a level set in the former methods.
cs/0609111
A State-Based Regression Formulation for Domains with Sensing Actions<br> and Incomplete Information
cs.AI
We present a state-based regression function for planning domains where an agent does not have complete information and may have sensing actions. We consider binary domains and employ a three-valued characterization of domains with sensing actions to define the regression function. We prove the soundness and completeness of our regression formulation with respect to the definition of progression. More specifically, we show that (i) a plan obtained through regression for a planning problem is indeed a progression solution of that planning problem, and that (ii) for each plan found through progression, using regression one obtains that plan or an equivalent one.
cs/0609112
A Richer Understanding of the Complexity of Election Systems
cs.GT cs.CC cs.MA
We provide an overview of some recent progress on the complexity of election systems. The issues studied include the complexity of the winner, manipulation, bribery, and control problems.
cs/0609117
Constructing LDPC Codes by 2-Lifts
cs.IT math.IT
We propose a new low-density parity-check code construction scheme based on 2-lifts. The proposed codes have an advantage of admitting efficient hardware implementations. With the motivation of designing codes with low error floors, we present an analysis of the low-weight stopping set distributions of the proposed codes. Based on this analysis, we propose design criteria for designing codes with low error floors. Numerical results show that the resulting codes have low error probabilities over binary erasure channels.
cs/0609119
Verification, Validation and Integrity of Distributed and Interchanged Rule Based Policies and Contracts in the Semantic Web
cs.AI cs.SE
Rule-based policy and contract systems have rarely been studied in terms of their software engineering properties. This is a serious omission, because in rule-based policy or contract representation languages rules are being used as a declarative programming language to formalize real-world decision logic and create IS production systems upon. This paper adopts an SE methodology from extreme programming, namely test driven development, and discusses how it can be adapted to verification, validation and integrity testing (V&V&I) of policy and contract specifications. Since, the test-driven approach focuses on the behavioral aspects and the drawn conclusions instead of the structure of the rule base and the causes of faults, it is independent of the complexity of the rule language and the system under test and thus much easier to use and understand for the rule engineer and the user.
cs/0609120
Rule-based Knowledge Representation for Service Level Agreement
cs.AI cs.DB cs.LO cs.MA cs.SE
Automated management and monitoring of service contracts like Service Level Agreements (SLAs) or higher-level policies is vital for efficient and reliable distributed service-oriented architectures (SOA) with high quality of ser-vice (QoS) levels. IT service provider need to manage, execute and maintain thousands of SLAs for different customers and different types of services, which needs new levels of flexibility and automation not available with the current technol-ogy. I propose a novel rule-based knowledge representation (KR) for SLA rules and a respective rule-based service level management (RBSLM) framework. My rule-based approach based on logic programming provides several advantages including automated rule chaining allowing for compact knowledge representation and high levels of automation as well as flexibility to adapt to rapidly changing business requirements. Therewith, I address an urgent need service-oriented busi-nesses do have nowadays which is to dynamically change their business and contractual logic in order to adapt to rapidly changing business environments and to overcome the restricting nature of slow change cycles.
cs/0609121
Approximating Rate-Distortion Graphs of Individual Data: Experiments in Lossy Compression and Denoising
cs.IT math.IT
Classical rate-distortion theory requires knowledge of an elusive source distribution. Instead, we analyze rate-distortion properties of individual objects using the recently developed algorithmic rate-distortion theory. The latter is based on the noncomputable notion of Kolmogorov complexity. To apply the theory we approximate the Kolmogorov complexity by standard data compression techniques, and perform a number of experiments with lossy compression and denoising of objects from different domains. We also introduce a natural generalization to lossy compression with side information. To maintain full generality we need to address a difficult searching problem. While our solutions are therefore not time efficient, we do observe good denoising and compression performance.
cs/0609122
Multi-Antenna Cooperative Wireless Systems: A Diversity-Multiplexing Tradeoff Perspective
cs.IT math.IT
We consider a general multiple antenna network with multiple sources, multiple destinations and multiple relays in terms of the diversity-multiplexing tradeoff (DMT). We examine several subcases of this most general problem taking into account the processing capability of the relays (half-duplex or full-duplex), and the network geometry (clustered or non-clustered). We first study the multiple antenna relay channel with a full-duplex relay to understand the effect of increased degrees of freedom in the direct link. We find DMT upper bounds and investigate the achievable performance of decode-and-forward (DF), and compress-and-forward (CF) protocols. Our results suggest that while DF is DMT optimal when all terminals have one antenna each, it may not maintain its good performance when the degrees of freedom in the direct link is increased, whereas CF continues to perform optimally. We also study the multiple antenna relay channel with a half-duplex relay. We show that the half-duplex DMT behavior can significantly be different from the full-duplex case. We find that CF is DMT optimal for half-duplex relaying as well, and is the first protocol known to achieve the half-duplex relay DMT. We next study the multiple-access relay channel (MARC) DMT. Finally, we investigate a system with a single source-destination pair and multiple relays, each node with a single antenna, and show that even under the idealistic assumption of full-duplex relays and a clustered network, this virtual multi-input multi-output (MIMO) system can never fully mimic a real MIMO DMT. For cooperative systems with multiple sources and multiple destinations the same limitation remains to be in effect.
cs/0609123
Optimal Design of Multiple Description Lattice Vector Quantizers
cs.IT math.IT
In the design of multiple description lattice vector quantizers (MDLVQ), index assignment plays a critical role. In addition, one also needs to choose the Voronoi cell size of the central lattice v, the sublattice index N, and the number of side descriptions K to minimize the expected MDLVQ distortion, given the total entropy rate of all side descriptions Rt and description loss probability p. In this paper we propose a linear-time MDLVQ index assignment algorithm for any K >= 2 balanced descriptions in any dimensions, based on a new construction of so-called K-fraction lattice. The algorithm is greedy in nature but is proven to be asymptotically (N -> infinity) optimal for any K >= 2 balanced descriptions in any dimensions, given Rt and p. The result is stronger when K = 2: the optimality holds for finite N as well, under some mild conditions. For K > 2, a local adjustment algorithm is developed to augment the greedy index assignment, and conjectured to be optimal for finite N. Our algorithmic study also leads to better understanding of v, N and K in optimal MDLVQ design. For K = 2 we derive, for the first time, a non-asymptotical closed form expression of the expected distortion of optimal MDLVQ in p, Rt, N. For K > 2, we tighten the current asymptotic formula of the expected distortion, relating the optimal values of N and K to p and Rt more precisely.
cs/0609125
Problem Evolution: A new approach to problem solving systems
cs.NE
In this paper we present a novel tool to evaluate problem solving systems. Instead of using a system to solve a problem, we suggest using the problem to evaluate the system. By finding a numerical representation of a problem's complexity, one can implement genetic algorithm to search for the most complex problem the given system can solve. This allows a comparison between different systems that solve the same set of problems. In this paper we implement this approach on pattern recognition neural networks to try and find the most complex pattern a given configuration can solve. The complexity of the pattern is calculated using linguistic complexity. The results demonstrate the power of the problem evolution approach in ranking different neural network configurations according to their pattern recognition abilities. Future research and implementations of this technique are also discussed.
cs/0609132
Semantic Description of Parameters in Web Service Annotations
cs.AI
A modification of OWL-S regarding parameter description is proposed. It is strictly based on Description Logic. In addition to class description of parameters it also allows the modelling of relations between parameters and the precise description of the size of data to be supplied to a service. In particular, it solves two major issues identified within current proposals for a Semantic Web Service annotation standard.
cs/0609133
An application-oriented terminology evaluation: the case of back-of-the book indexes
cs.AI cs.IR
This paper addresses the problem of computational terminology evaluation not per se but in a specific application context. This paper describes the evaluation procedure that has been used to assess the validity of our overall indexing approach and the quality of the IndDoc indexing tool. Even if user-oriented extended evaluation is irreplaceable, we argue that early evaluations are possible and they are useful for development guidance.
cs/0609134
Using NLP to build the hypertextuel network of a back-of-the-book index
cs.AI cs.IR
Relying on the idea that back-of-the-book indexes are traditional devices for navigation through large documents, we have developed a method to build a hypertextual network that helps the navigation in a document. Building such an hypertextual network requires selecting a list of descriptors, identifying the relevant text segments to associate with each descriptor and finally ranking the descriptors and reference segments by relevance order. We propose a specific document segmentation method and a relevance measure for information ranking. The algorithms are tested on 4 corpora (of different types and domains) without human intervention or any semantic knowledge.
cs/0609135
Event-based Information Extraction for the biomedical domain: the Caderige project
cs.AI cs.IR
This paper gives an overview of the Caderige project. This project involves teams from different areas (biology, machine learning, natural language processing) in order to develop high-level analysis tools for extracting structured information from biological bibliographical databases, especially Medline. The paper gives an overview of the approach and compares it to the state of the art.
cs/0609136
The ALVIS Format for Linguistically Annotated Documents
cs.AI
The paper describes the ALVIS annotation format designed for the indexing of large collections of documents in topic-specific search engines. This paper is exemplified on the biological domain and on MedLine abstracts, as developing a specialized search engine for biologists is one of the ALVIS case studies. The ALVIS principle for linguistic annotations is based on existing works and standard propositions. We made the choice of stand-off annotations rather than inserted mark-up. Annotations are encoded as XML elements which form the linguistic subsection of the document record.
cs/0609137
Ontologies and Information Extraction
cs.AI cs.IR
This report argues that, even in the simplest cases, IE is an ontology-driven process. It is not a mere text filtering method based on simple pattern matching and keywords, because the extracted pieces of texts are interpreted with respect to a predefined partial domain model. This report shows that depending on the nature and the depth of the interpretation to be done for extracting the information, more or less knowledge must be involved. This report is mainly illustrated in biology, a domain in which there are critical needs for content-based exploration of the scientific literature and which becomes a major application domain for IE.
cs/0609138
MDL Denoising Revisited
cs.IT math.IT
We refine and extend an earlier MDL denoising criterion for wavelet-based denoising. We start by showing that the denoising problem can be reformulated as a clustering problem, where the goal is to obtain separate clusters for informative and non-informative wavelet coefficients, respectively. This suggests two refinements, adding a code-length for the model index, and extending the model in order to account for subband-dependent coefficient distributions. A third refinement is derivation of soft thresholding inspired by predictive universal coding with weighted mixtures. We propose a practical method incorporating all three refinements, which is shown to achieve good performance and robustness in denoising both artificial and natural signals.
cs/0609139
The Capacity of Channels with Feedback
cs.IT math.IT
We introduce a general framework for treating channels with memory and feedback. First, we generalize Massey's concept of directed information and use it to characterize the feedback capacity of general channels. Second, we present coding results for Markov channels. This requires determining appropriate sufficient statistics at the encoder and decoder. Third, a dynamic programming framework for computing the capacity of Markov channels is presented. Fourth, it is shown that the average cost optimality equation (ACOE) can be viewed as an implicit single-letter characterization of the capacity. Fifth, scenarios with simple sufficient statistics are described.
cs/0609140
Motion Primitives for Robotic Flight Control
cs.RO cs.LG
We introduce a simple framework for learning aggressive maneuvers in flight control of UAVs. Having inspired from biological environment, dynamic movement primitives are analyzed and extended using nonlinear contraction theory. Accordingly, primitives of an observed movement are stably combined and concatenated. We demonstrate our results experimentally on the Quanser Helicopter, in which we first imitate aggressive maneuvers and then use them as primitives to achieve new maneuvers that can fly over an obstacle.
cs/0609142
Modular self-organization
cs.AI
The aim of this paper is to provide a sound framework for addressing a difficult problem: the automatic construction of an autonomous agent's modular architecture. We combine results from two apparently uncorrelated domains: Autonomous planning through Markov Decision Processes and a General Data Clustering Approach using a kernel-like method. Our fundamental idea is that the former is a good framework for addressing autonomy whereas the latter allows to tackle self-organizing problems.
cs/0609143
ECA-LP / ECA-RuleML: A Homogeneous Event-Condition-Action Logic Programming Language
cs.AI cs.LO cs.SE
Event-driven reactive functionalities are an urgent need in nowadays distributed service-oriented applications and (Semantic) Web-based environments. An important problem to be addressed is how to correctly and efficiently capture and process the event-based behavioral, reactive logic represented as ECA rules in combination with other conditional decision logic which is represented as derivation rules. In this paper we elaborate on a homogeneous integration approach which combines derivation rules, reaction rules (ECA rules) and other rule types such as integrity constraint into the general framework of logic programming. The developed ECA-LP language provides expressive features such as ID-based updates with support for external and self-updates of the intensional and extensional knowledge, transac-tions including integrity testing and an event algebra to define and process complex events and actions based on a novel interval-based Event Calculus variant.
cs/0609144
The Management and Integration of Biomedical Knowledge: Application in the Health-e-Child Project (Position Paper)
cs.DB
The Health-e-Child project aims to develop an integrated healthcare platform for European paediatrics. In order to achieve a comprehensive view of childrens health, a complex integration of biomedical data, information, and knowledge is necessary. Ontologies will be used to formally define this domain knowledge and will form the basis for the medical knowledge management system. This paper introduces an innovative methodology for the vertical integration of biomedical knowledge. This approach will be largely clinician-centered and will enable the definition of ontology fragments, connections between them (semantic bridges) and enriched ontology fragments (views). The strategy for the specification and capture of fragments, bridges and views is outlined with preliminary examples demonstrated in the collection of biomedical information from hospital databases, biomedical ontologies, and biomedical public databases.
cs/0609145
A Semidefinite Relaxation for Air Traffic Flow Scheduling
cs.CE
We first formulate the problem of optimally scheduling air traffic low with sector capacity constraints as a mixed integer linear program. We then use semidefinite relaxation techniques to form a convex relaxation of that problem. Finally, we present a randomization algorithm to further improve the quality of the solution. Because of the specific structure of the air traffic flow problem, the relaxation has a single semidefinite constraint of size dn where d is the maximum delay and n the number of flights.
cs/0609146
A Combinatorial Family of Near Regular LDPC Codes
cs.IT math.IT
An elementary combinatorial Tanner graph construction for a family of near-regular low density parity check codes achieving high girth is presented. The construction allows flexibility in the choice of design parameters like rate, average degree, girth and block length of the code and yields an asymptotic family. The complexity of constructing codes in the family grows only quadratically with the block length.
cs/0609148
Pseudo-Codeword Performance Analysis for LDPC Convolutional Codes
cs.IT math.IT
Message-passing iterative decoders for low-density parity-check (LDPC) block codes are known to be subject to decoding failures due to so-called pseudo-codewords. These failures can cause the large signal-to-noise ratio performance of message-passing iterative decoding to be worse than that predicted by the maximum-likelihood decoding union bound. In this paper we address the pseudo-codeword problem from the convolutional-code perspective. In particular, we compare the performance of LDPC convolutional codes with that of their ``wrapped'' quasi-cyclic block versions and we show that the minimum pseudo-weight of an LDPC convolutional code is at least as large as the minimum pseudo-weight of an underlying quasi-cyclic code. This result, which parallels a well-known relationship between the minimum Hamming weight of convolutional codes and the minimum Hamming weight of their quasi-cyclic counterparts, is due to the fact that every pseudo-codeword in the convolutional code induces a pseudo-codeword in the block code with pseudo-weight no larger than that of the convolutional code's pseudo-codeword. This difference in the weight spectra leads to improved performance at low-to-moderate signal-to-noise ratios for the convolutional code, a conclusion supported by simulation results.
cs/0609153
Mining Generalized Graph Patterns based on User Examples
cs.DS cs.LG
There has been a lot of recent interest in mining patterns from graphs. Often, the exact structure of the patterns of interest is not known. This happens, for example, when molecular structures are mined to discover fragments useful as features in chemical compound classification task, or when web sites are mined to discover sets of web pages representing logical documents. Such patterns are often generated from a few small subgraphs (cores), according to certain generalization rules (GRs). We call such patterns "generalized patterns"(GPs). While being structurally different, GPs often perform the same function in the network. Previously proposed approaches to mining GPs either assumed that the cores and the GRs are given, or that all interesting GPs are frequent. These are strong assumptions, which often do not hold in practical applications. In this paper, we propose an approach to mining GPs that is free from the above assumptions. Given a small number of GPs selected by the user, our algorithm discovers all GPs similar to the user examples. First, a machine learning-style approach is used to find the cores. Second, generalizations of the cores in the graph are computed to identify GPs. Evaluation on synthetic data, generated using real cores and GRs from biological and web domains, demonstrates effectiveness of our approach.
cs/0609154
Loop Calculus Helps to Improve Belief Propagation and Linear Programming Decodings of Low-Density-Parity-Check Codes
cs.IT cond-mat.dis-nn cond-mat.stat-mech math.IT
We illustrate the utility of the recently developed loop calculus for improving the Belief Propagation (BP) algorithm. If the algorithm that minimizes the Bethe free energy fails we modify the free energy by accounting for a critical loop in a graphical representation of the code. The log-likelihood specific critical loop is found by means of the loop calculus. The general method is tested using an example of the Linear Programming (LP) decoding, that can be viewed as a special limit of the BP decoding. Considering the (155,64,20) code that performs over Additive-White-Gaussian-Noise channel we show that the loop calculus improves the LP decoding and corrects all previously found dangerous configurations of log-likelihoods related to pseudo-codewords with low effective distance, thus reducing the code's error-floor.
cs/0609155
Detection of Markov Random Fields on Two-Dimensional Intersymbol Interference Channels
cs.IT math.IT
We present a novel iterative algorithm for detection of binary Markov random fields (MRFs) corrupted by two-dimensional (2D) intersymbol interference (ISI) and additive white Gaussian noise (AWGN). We assume a first-order binary MRF as a simple model for correlated images. We assume a 2D digital storage channel, where the MRF is interleaved before being written and then read by a 2D transducer; such channels occur in recently proposed optical disk storage systems. The detection algorithm is a concatenation of two soft-input/soft-output (SISO) detectors: an iterative row-column soft-decision feedback (IRCSDF) ISI detector, and a MRF detector. The MRF detector is a SISO version of the stochastic relaxation algorithm by Geman and Geman in IEEE Trans. Pattern Anal. and Mach. Intell., Nov. 1984. On the 2 x 2 averaging-mask ISI channel, at a bit error rate (BER) of 10^{-5}, the concatenated algorithm achieves SNR savings of between 0.5 and 2.0 dB over the IRCSDF detector alone; the savings increase as the MRFs become more correlated, or as the SNR decreases. The algorithm is also fairly robust to mismatches between the assumed and actual MRF parameters.
cs/0609156
Entangled Graphs
cs.IT cs.DM math.IT
In this paper we prove a separability criterion for mixed states in $\mathbb C^p\otimes\mathbb C^q$. We also show that the density matrix of a graph with only one entangled edge is entangled.
cs/0609157
Sensor Scheduling for Optimal Observability Using Estimation Entropy
cs.IT cs.AI math.IT
We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process is observed by a single sensor which needs to be dynamically adjusted or by a set of sensors which are selected one at a time in a way that maximizes the information acquisition from the process. Similar to conventional POMDP problems, in this model the control action is based on all past measurements; however here this action is not for the control of state process, which is autonomous, but it is for influencing the measurement of that process. This POMDP is a controlled version of the hidden Markov process, and we show that its optimal observability problem can be formulated as an average cost Markov decision process (MDP) scheduling problem. In this problem, a policy is a rule for selecting sensors or adjusting the measuring device based on the measurement history. Given a policy, we can evaluate the estimation entropy for the joint state-measurement processes which inversely measures the observability of state process for that policy. Considering estimation entropy as the cost of a policy, we show that the problem of finding optimal policy is equivalent to an average cost MDP scheduling problem where the cost function is the entropy function over the belief space. This allows the application of the policy iteration algorithm for finding the policy achieving minimum estimation entropy, thus optimum observability.
cs/0609159
Duality for Several Families of Evaluation Codes
cs.IT cs.DM math.IT
We consider generalizations of Reed-Muller codes, toric codes, and codes from certain plane curves, such as those defined by norm and trace functions on finite fields. In each case we are interested in codes defined by evaluating arbitrary subsets of monomials, and in identifying when the dual codes are also obtained by evaluating monomials. We then move to the context of order domain theory, in which the subsets of monomials can be chosen to optimize decoding performance using the Berlekamp-Massey-Sakata algorithm with majority voting. We show that for the codes under consideration these subsets are well-behaved and the dual codes are also defined by monomials.
cs/0609160
Redundancies of Correction-Capability-Optimized Reed-Muller Codes
cs.IT cs.DM math.IT
This article is focused on some variations of Reed-Muller codes that yield improvements to the rate for a prescribed decoding performance under the Berlekamp-Massey-Sakata algorithm with majority voting. Explicit formulas for the redundancies of the new codes are given.
cs/0609161
The Order Bound on the Minimum Distance of the One-Point Codes Associated to a Garcia-Stichtenoth Tower of Function Fields
cs.IT cs.DM math.IT
Garcia and Stichtenoth discovered two towers of function fields that meet the Drinfeld-Vl\u{a}du\c{t} bound on the ratio of the number of points to the genus. For one of these towers, Garcia, Pellikaan and Torres derived a recursive description of the Weierstrass semigroups associated to a tower of points on the associated curves. In this article, a non-recursive description of the semigroups is given and from this the enumeration of each of the semigroups is derived as well as its inverse. This enables us to find an explicit formula for the order (Feng-Rao) bound on the minimum distance of the associated one-point codes.
cs/0609162
On Semigroups Generated by Two Consecutive Integers and Improved Hermitian Codes
cs.IT cs.DM math.IT
Analysis of the Berlekamp-Massey-Sakata algorithm for decoding one-point codes leads to two methods for improving code rate. One method, due to Feng and Rao, removes parity checks that may be recovered by their majority voting algorithm. The second method is to design the code to correct only those error vectors of a given weight that are also geometrically generic. In this work, formulae are given for the redundancies of Hermitian codes optimized with respect to these criteria as well as the formula for the order bound on the minimum distance. The results proceed from an analysis of numerical semigroups generated by two consecutive integers. The formula for the redundancy of optimal Hermitian codes correcting a given number of errors answers an open question stated by Pellikaan and Torres in 1999.
cs/0609164
Conditional Expressions for Blind Deconvolution: Multi-point form
cs.CV
We present conditional expression (CE) for finding blurs convolved in given images. The CE is given in terms of the zero-values of the blurs evaluated at multi-point. The CE can detect multiple blur all at once. We illustrate the multiple blur-detection by using a test image.
cs/0609165
Simple method to eliminate blur based on Lane and Bates algorithm
cs.CV
A simple search method for finding a blur convolved in a given image is presented. The method can be easily extended to a large blur. The method has been experimentally tested with a model blurred image.
cs/0610002
Conditional Expressions for Blind Deconvolution: Derivative form
cs.CV
We developed novel conditional expressions (CEs) for Lane and Bates' blind deconvolution. The CEs are given in term of the derivatives of the zero-values of the z-transform of given images. The CEs make it possible to automatically detect multiple blur convolved in the given images all at once without performing any analysis of the zero-sheets of the given images. We illustrate the multiple blur-detection by the CEs for a model image
cs/0610004
Rapport technique du projet OGRE
cs.CL cs.AI
This repport concerns automatic understanding of (french) iterative sentences, i.e. sentences where one single verb has to be interpreted by a more or less regular plurality of events. A linguistic analysis is proposed along an extension of Reichenbach's theory, several formal representations are considered and a corpus of 18000 newspaper extracts is described.
cs/0610006
A Typed Hybrid Description Logic Programming Language with Polymorphic Order-Sorted DL-Typed Unification for Semantic Web Type Systems
cs.AI
In this paper we elaborate on a specific application in the context of hybrid description logic programs (hybrid DLPs), namely description logic Semantic Web type systems (DL-types) which are used for term typing of LP rules based on a polymorphic, order-sorted, hybrid DL-typed unification as procedural semantics of hybrid DLPs. Using Semantic Web ontologies as type systems facilitates interchange of domain-independent rules over domain boundaries via dynamically typing and mapping of explicitly defined type ontologies.
cs/0610007
Full Text Searching in the Astrophysics Data System
cs.DL astro-ph cs.DB
The Smithsonian/NASA Astrophysics Data System (ADS) provides a search system for the astronomy and physics scholarly literature. All major and many smaller astronomy journals that were published on paper have been scanned back to volume 1 and are available through the ADS free of charge. All scanned pages have been converted to text and can be searched through the ADS Full Text Search System. In addition, searches can be fanned out to several external search systems to include the literature published in electronic form. Results from the different search systems are combined into one results list. The ADS Full Text Search System is available at: http://adsabs.harvard.edu/fulltext_service.html
cs/0610008
Connectivity in the Astronomy Digital Library
cs.DL astro-ph cs.DB
The Astrophysics Data System (ADS) provides an extensive system of links between the literature and other on-line information. Recently, the journals of the American Astronomical Society (AAS) and a group of NASA data centers have collaborated to provide more links between on-line data obtained by space missions and the on-line journals. Authors can now specify which data sets they have used in their article. This information is used by the participants to provide the links between the literature and the data. The ADS is available at: http://ads.harvard.edu
cs/0610010
One-Pass, One-Hash n-Gram Statistics Estimation
cs.DB cs.CL
In multimedia, text or bioinformatics databases, applications query sequences of n consecutive symbols called n-grams. Estimating the number of distinct n-grams is a view-size estimation problem. While view sizes can be estimated by sampling under statistical assumptions, we desire an unassuming algorithm with universally valid accuracy bounds. Most related work has focused on repeatedly hashing the data, which is prohibitive for large data sources. We prove that a one-pass one-hash algorithm is sufficient for accurate estimates if the hashing is sufficiently independent. To reduce costs further, we investigate recursive random hashing algorithms and show that they are sufficiently independent in practice. We compare our running times with exact counts using suffix arrays and show that, while we use hardly any storage, we are an order of magnitude faster. The approach further is extended to a one-pass/one-hash computation of n-gram entropy and iceberg counts. The experiments use a large collection of English text from the Gutenberg Project as well as synthetic data.
cs/0610011
Creation and use of Citations in the ADS
cs.DL astro-ph cs.DB cs.IR
With over 20 million records, the ADS citation database is regularly used by researchers and librarians to measure the scientific impact of individuals, groups, and institutions. In addition to the traditional sources of citations, the ADS has recently added references extracted from the arXiv e-prints on a nightly basis. We review the procedures used to harvest and identify the reference data used in the creation of citations, the policies and procedures that we follow to avoid double-counting and to eliminate contributions which may not be scholarly in nature. Finally, we describe how users and institutions can easily obtain quantitative citation data from the ADS, both interactively and via web-based programming tools. The ADS is available at http://ads.harvard.edu.
cs/0610012
On Shift Sequences for Interleaved Construction of Sequence Sets with Low Correlation
cs.IT math.IT
Construction of signal sets with low correlation property is of interest to designers of CDMA systems. One of the preferred ways of constructing such sets is the interleaved construction which uses two sequences a and b with 2-level autocorrelation and a shift sequence e. The shift sequence has to satisfy certain conditions for the resulting signal set to have low correlation properties. This article shows that the conditions reported in literature are too strong and gives a version which results in more number of shift sequences. An open problem on the existence of shift sequences for attaining an interleaved set with maximum correlation value bounded by v+2 is also taken up and solved.
cs/0610015
Why did the accident happen? A norm-based reasoning approach
cs.AI
In this paper we describe an architecture of a system that answer the question : Why did the accident happen? from the textual description of an accident. We present briefly the different parts of the architecture and then we describe with more detail the semantic part of the system i.e. the part in which the norm-based reasoning is performed on the explicit knowlege extracted from the text.
cs/0610016
Norm Based Causal Reasoning in Textual Corpus
cs.AI cs.CL
Truth based entailments are not sufficient for a good comprehension of NL. In fact, it can not deduce implicit information necessary to understand a text. On the other hand, norm based entailments are able to reach this goal. This idea was behind the development of Frames (Minsky 75) and Scripts (Schank 77, Schank 79) in the 70's. But these theories are not formalized enough and their adaptation to new situations is far from being obvious. In this paper, we present a reasoning system which uses norms in a causal reasoning process in order to find the cause of an accident from a text describing it.
cs/0610018
Raisonnement stratifi\'{e} \`{a} base de normes pour inf\'{e}rer les causes dans un corpus textuel
cs.AI cs.CL
To understand texts written in natural language (LN), we use our knowledge about the norms of the domain. Norms allow to infer more implicit information from the text. This kind of information can, in general, be defeasible, but it remains useful and acceptable while the text do not contradict it explicitly. In this paper we describe a non-monotonic reasoning system based on the norms of the car crash domain. The system infers the cause of an accident from its textual description. The cause of an accident is seen as the most specific norm which has been violated. The predicates and the rules of the system are stratified: organized on layers in order to obtain an efficient reasoning.
cs/0610019
NectaRSS, an RSS feed ranking system that implicitly learns user preferences
cs.IR cs.HC
In this paper a new RSS feed ranking method called NectaRSS is introduced. The system recommends information to a user based on his/her past choices. User preferences are automatically acquired, avoiding explicit feedback, and ranking is based on those preferences distilled to a user profile. NectaRSS uses the well-known vector space model for user profiles and new documents, and compares them using information-retrieval techniques, but introduces a novel method for user profile creation and adaptation from users' past choices. The efficiency of the proposed method has been tested by embedding it into an intelligent aggregator (RSS feed reader), which has been used by different and heterogeneous users. Besides, this paper proves that the ranking of newsitems yielded by NectaRSS improves its quality with user's choices, and its superiority over other algorithms that use a different information representation method.
cs/0610020
XString: XML as a String
cs.DB
Extensible markup language (XML) is a technology that has been much hyped, so that XML has become an industry buzzword. Behind the hype is a powerful technology for data representation in a platform independent manner. As a text document, however, XML suffers from being too bloated, and requires an XML parser to access and manipulate it. XString is an encoding method for XML, in essence, a markup language's markup language. XString gives the benefit of compressing XML, and allows for easy manipulation and processing of XML source as a very long string.
cs/0610021
On the Fading Paper Achievable Region of the Fading MIMO Broadcast Channel
cs.IT math.IT
We consider transmission over the ergodic fading multi-antenna broadcast (MIMO-BC) channel with partial channel state information at the transmitter and full information at the receiver. Over the equivalent {\it non}-fading channel, capacity has recently been shown to be achievable using transmission schemes that were designed for the ``dirty paper'' channel. We focus on a similar ``fading paper'' model. The evaluation of the fading paper capacity is difficult to obtain. We confine ourselves to the {\it linear-assignment} capacity, which we define, and use convex analysis methods to prove that its maximizing distribution is Gaussian. We compare our fading-paper transmission to an application of dirty paper coding that ignores the partial state information and assumes the channel is fixed at the average fade. We show that a gain is easily achieved by appropriately exploiting the information. We also consider a cooperative upper bound on the sum-rate capacity as suggested by Sato. We present a numeric example that indicates that our scheme is capable of realizing much of this upper bound.
cs/0610022
Iterative Decoding of Low-Density Parity Check Codes (A Survey)
cs.IT cs.CC math.IT
Much progress has been made on decoding algorithms for error-correcting codes in the last decade. In this article, we give an introduction to some fundamental results on iterative, message-passing algorithms for low-density parity check codes. For certain important stochastic channels, this line of work has enabled getting very close to Shannon capacity with algorithms that are extremely efficient (both in theory and practice).
cs/0610023
Une exp\'{e}rience de s\'{e}mantique inf\'{e}rentielle
cs.AI
We develop a system which must be able to perform the same inferences that a human reader of an accident report can do and more particularly to determine the apparent causes of the accident. We describe the general framework in which we are situated, linguistic and semantic levels of the analysis and the inference rules used by the system.
cs/0610025
Low Correlation Sequences over the QAM Constellation
cs.IT math.IT
This paper presents the first concerted look at low correlation sequence families over QAM constellations of size M^2=4^m and their potential applicability as spreading sequences in a CDMA setting. Five constructions are presented, and it is shown how such sequence families have the ability to transport a larger amount of data as well as enable variable-rate signalling on the reverse link. Canonical family CQ has period N, normalized maximum-correlation parameter theta_max bounded above by A sqrt(N), where 'A' ranges from 1.8 in the 16-QAM case to 3.0 for large M. In a CDMA setting, each user is enabled to transfer 2m bits of data per period of the spreading sequence which can be increased to 3m bits of data by halving the size of the sequence family. The technique used to construct CQ is easily extended to produce larger sequence families and an example is provided. Selected family SQ has a lower value of theta_max but permits only (m+1)-bit data modulation. The interleaved 16-QAM sequence family IQ has theta_max <= sqrt(2) sqrt(N) and supports 3-bit data modulation. The remaining two families are over a quadrature-PAM (Q-PAM) subset of size 2M of the M^2-QAM constellation. Family P has a lower value of theta_max in comparison with Family SQ, while still permitting (m+1)-bit data modulation. Interleaved family IP, over the 8-ary Q-PAM constellation, permits 3-bit data modulation and interestingly, achieves the Welch lower bound on theta_max.
cs/0610029
Data in the ADS -- Understanding How to Use it Better
cs.DL cs.DB
The Smithsonian/NASA ADS Abstract Service contains a wealth of data for astronomers and librarians alike, yet the vast majority of usage consists of rudimentary searches. Hints on how to obtain more focused search results by using more of the various capabilities of the ADS are presented, including searching by affiliation. We also discuss the classification of articles by content and by referee status. The ADS is funded by NASA Grant NNG06GG68G-16613687.
cs/0610033
A kernel for time series based on global alignments
cs.CV cs.LG
We propose in this paper a new family of kernels to handle times series, notably speech data, within the framework of kernel methods which includes popular algorithms such as the Support Vector Machine. These kernels elaborate on the well known Dynamic Time Warping (DTW) family of distances by considering the same set of elementary operations, namely substitutions and repetitions of tokens, to map a sequence onto another. Associating to each of these operations a given score, DTW algorithms use dynamic programming techniques to compute an optimal sequence of operations with high overall score. In this paper we consider instead the score spanned by all possible alignments, take a smoothed version of their maximum and derive a kernel out of this formulation. We prove that this kernel is positive definite under favorable conditions and show how it can be tuned effectively for practical applications as we report encouraging results on a speech recognition task.
cs/0610037
The Capacity Region of a Class of Discrete Degraded Interference Channels
cs.IT math.IT
We provide a single-letter characterization for the capacity region of a class of discrete degraded interference channels (DDICs). The class of DDICs considered includes the discrete additive degraded interference channel (DADIC) studied by Benzel. We show that for the class of DDICs studied, encoder cooperation does not increase the capacity region, and therefore, the capacity region of the class of DDICs is the same as the capacity region of the corresponding degraded broadcast channel.
cs/0610039
The Application of Fuzzy Logic to the Construction of the Ranking Function of Information Retrieval Systems
cs.IR cs.AI
The quality of the ranking function is an important factor that determines the quality of the Information Retrieval system. Each document is assigned a score by the ranking function; the score indicates the likelihood of relevance of the document given a query. In the vector space model, the ranking function is defined by a mathematic expression. We propose a fuzzy logic (FL) approach to defining the ranking function. FL provides a convenient way of converting knowledge expressed in a natural language into fuzzy logic rules. The resulting ranking function could be easily viewed, extended, and verified: * if (tf is high) and (idf is high) > (relevance is high); * if (overlap is high) > (relevance is high). By using above FL rules, we are able to achieve performance approximately equal to the state of the art search engine Apache Lucene (deltaP10 +0.92%; deltaMAP -0.1%). The fuzzy logic approach allows combining the logic-based model with the vector model. The resulting model possesses simplicity and formalism of the logic based model, and the flexibility and performance of the vector model.
cs/0610041
A Computational Model of Spatial Memory Anticipation during Visual Search
cs.NE
Some visual search tasks require to memorize the location of stimuli that have been previously scanned. Considerations about the eye movements raise the question of how we are able to maintain a coherent memory, despite the frequent drastically changes in the perception. In this article, we present a computational model that is able to anticipate the consequences of the eye movements on the visual perception in order to update a spatial memory
cs/0610043
Farthest-Point Heuristic based Initialization Methods for K-Modes Clustering
cs.AI
The k-modes algorithm has become a popular technique in solving categorical data clustering problems in different application domains. However, the algorithm requires random selection of initial points for the clusters. Different initial points often lead to considerable distinct clustering results. In this paper we present an experimental study on applying a farthest-point heuristic based initialization method to k-modes clustering to improve its performance. Experiments show that new initialization method leads to better clustering accuracy than random selection initialization method for k-modes clustering.
cs/0610045
Spectra of large block matrices
cs.IT math.IT math.OA
In a frequency selective slow-fading channel in a MIMO system, the channel matrix is of the form of a block matrix. This paper proposes a method to calculate the limit of the eigenvalue distribution of block matrices if the size of the blocks tends to infinity. While it considers random matrices, it takes an operator-valued free probability approach to achieve this goal. Using this method, one derives a system of equations, which can be solved numerically to compute the desired eigenvalue distribution. The paper initially tackles the problem for square block matrices, then extends the solution to rectangular block matrices. Finally, it deals with Wishart type block matrices. For two special cases, the results of our approach are compared with results from simulations. The first scenario investigates the limit eigenvalue distribution of block Toeplitz matrices. The second scenario deals with the distribution of Wishart type block matrices for a frequency selective slow-fading channel in a MIMO system for two different cases of $n_R=n_T$ and $n_R=2n_T$. Using this method, one may calculate the capacity and the Signal-to-Interference-and-Noise Ratio in large MIMO systems.
cs/0610047
Capacity of the Trapdoor Channel with Feedback
cs.IT math.IT
We establish that the feedback capacity of the trapdoor channel is the logarithm of the golden ratio and provide a simple communication scheme that achieves capacity. As part of the analysis, we formulate a class of dynamic programs that characterize capacities of unifilar finite-state channels. The trapdoor channel is an instance that admits a simple analytic solution.
cs/0610050
The Mathematical Parallels Between Packet Switching and Information Transmission
cs.IT cs.NI math.IT
All communication networks comprise of transmission systems and switching systems, even though they are usually treated as two separate issues. Communication channels are generally disturbed by noise from various sources. In circuit switched networks, reliable communication requires the error-tolerant transmission of bits over noisy channels. In packet switched networks, however, not only can bits be corrupted with noise, but resources along connection paths are also subject to contention. Thus, quality of service (QoS) is determined by buffer delays and packet losses. The theme of this paper is to show that transmission noise and packet contention actually have similar characteristics and can be tamed by comparable means to achieve reliable communication, and a number of analogies between switching and transmission are identified. The sampling theorem of bandlimited signals provides the cornerstone of digital communication and signal processing. Recently, the Birkhoff-von Neumann decomposition of traffic matrices has been widely applied to packet switches. With respect to the complexity reduction of packet switching, we show that the decomposition of a doubly stochastic traffic matrix plays a similar role to that of the sampling theorem in digital transmission. We conclude that packet switching systems are governed by mathematical laws that are similar to those of digital transmission systems as envisioned by Shannon in his seminal 1948 paper, A Mathematical Theory of Communication.
cs/0610052
Finite-Dimensional Bounds on Zm and Binary LDPC Codes with Belief Propagation Decoders
cs.IT math.IT
This paper focuses on finite-dimensional upper and lower bounds on decodable thresholds of Zm and binary low-density parity-check (LDPC) codes, assuming belief propagation decoding on memoryless channels. A concrete framework is presented, admitting systematic searches for new bounds. Two noise measures are considered: the Bhattacharyya noise parameter and the soft bit value for a maximum a posteriori probability (MAP) decoder on the uncoded channel. For Zm LDPC codes, an iterative m-dimensional bound is derived for m-ary-input/symmetric-output channels, which gives a sufficient stability condition for Zm LDPC codes and is complemented by a matched necessary stability condition introduced herein. Applications to coded modulation and to codes with non-equiprobable distributed codewords are also discussed. For binary codes, two new lower bounds are provided for symmetric channels, including a two-dimensional iterative bound and a one-dimensional non-iterative bound, the latter of which is the best known bound that is tight for binary symmetric channels (BSCs), and is a strict improvement over the bound derived by the channel degradation argument. By adopting the reverse channel perspective, upper and lower bounds on the decodable Bhattacharyya noise parameter are derived for non-symmetric channels, which coincides with the existing bound for symmetric channels.
cs/0610053
Towards a Bayesian framework for option pricing
cs.CE q-fin.PR
In this paper, we describe a general method for constructing the posterior distribution of an option price. Our framework takes as inputs the prior distributions of the parameters of the stochastic process followed by the underlying, as well as the likelihood function implied by the observed price history for the underlying. Our work extends that of Karolyi (1993) and Darsinos and Satchell (2001), but with the crucial difference that the likelihood function we use for inference is that which is directly implied by the underlying, rather than imposed in an ad hoc manner via the introduction of a function representing "measurement error." As such, an important problem still relevant for our method is that of model risk, and we address this issue by describing how to perform a Bayesian averaging of parameter inferences based on the different models considered using our framework.
cs/0610057
Properties of codes in rank metric
cs.DM cs.IT math.IT
We study properties of rank metric and codes in rank metric over finite fields. We show that in rank metric perfect codes do not exist. We derive an existence bound that is the equivalent of the Gilbert--Varshamov bound in Hamming metric. We study the asymptotic behavior of the minimum rank distance of codes satisfying GV. We derive the probability distribution of minimum rank distance for random and random $\F{q}$-linear codes. We give an asymptotic equivalent of their average minimum rank distance and show that random $\F{q}$-linear codes are on GV bound for rank metric. We show that the covering density of optimum codes whose codewords can be seen as square matrices is lower bounded by a function depending only on the error-correcting capability of the codes. We show that there are quasi-perfect codes in rank metric over fields of characteristic 2.
cs/0610058
Context-sensitive access to e-document corpus
cs.IR
The methodology of context-sensitive access to e-documents considers context as a problem model based on the knowledge extracted from the application domain, and presented in the form of application ontology. Efficient access to an information in the text form is needed. Wiki resources as a modern text format provides huge number of text in a semi formalized structure. At the first stage of the methodology, documents are indexed against the ontology representing macro-situation. The indexing method uses a topic tree as a middle layer between documents and the application ontology. At the second stage documents relevant to the current situation (the abstract and operational contexts) are identified and sorted by degree of relevance. Abstract context is a problem-oriented ontology-based model. Operational context is an instantiation of the abstract context with data provided by the information sources. The following parts of the methodology are described: (i) metrics for measuring similarity of e-documents to ontology, (ii) a document index storing results of indexing of e-documents against the ontology; (iii) a method for identification of relevant e-documents based on semantic similarity measures. Wikipedia (wiki resource) is used as a corpus of e-documents for approach evaluation in a case study. Text categorization, the presence of metadata, and an existence of a lot of articles related to different topics characterize the corpus.
cs/0610059
Camera motion estimation through planar deformation determination
cs.CV
In this paper, we propose a global method for estimating the motion of a camera which films a static scene. Our approach is direct, fast and robust, and deals with adjacent frames of a sequence. It is based on a quadratic approximation of the deformation between two images, in the case of a scene with constant depth in the camera coordinate system. This condition is very restrictive but we show that provided translation and depth inverse variations are small enough, the error on optical flow involved by the approximation of depths by a constant is small. In this context, we propose a new model of camera motion, that allows to separate the image deformation in a similarity and a ``purely'' projective application, due to change of optical axis direction. This model leads to a quadratic approximation of image deformation that we estimate with an M-estimator; we can immediatly deduce camera motion parameters.
cs/0610060
Comparing Typical Opening Move Choices Made by Humans and Chess Engines
cs.AI
The opening book is an important component of a chess engine, and thus computer chess programmers have been developing automated methods to improve the quality of their books. For chess, which has a very rich opening theory, large databases of high-quality games can be used as the basis of an opening book, from which statistics relating to move choices from given positions can be collected. In order to find out whether the opening books used by modern chess engines in machine versus machine competitions are ``comparable'' to those used by chess players in human versus human competitions, we carried out analysis on 26 test positions using statistics from two opening books one compiled from humans' games and the other from machines' games. Our analysis using several nonparametric measures, shows that, overall, there is a strong association between humans' and machines' choices of opening moves when using a book to guide their choices.
cs/0610061
The Delay-Limited Capacity Region of OFDM Broadcast Channels
cs.IT math.IT
In this work, the delay limited capacity (DLC) of orthogonal frequency division multiplexing (OFDM) systems is investigated. The analysis is organized into two parts. In the first part, the impact of system parameters on the OFDM DLC is analyzed in a general setting. The main results are that under weak assumptions the maximum achievable single user DLC is almost independent of the distribution of the path attenuations in the low signal-to-noise (SNR) region but depends strongly on the delay spread. In the high SNR region the roles are exchanged. Here, the impact of delay spread is negligible while the impact of the distribution becomes dominant. The relevant asymptotic quantities are derived without employing simplifying assumptions on the OFDM correlation structure. Moreover, for both cases it is shown that the DLC is maximized if the total channel energy is uniformly spread, i.e. the power delay profile is uniform. It is worth pointing out that since universal bounds are obtained the results can also be used for other classes of parallel channels with block fading characteristic. The second part extends the setting to the broadcast channel and studies the corresponding OFDM DLC BC region. An algorithm for computing the OFDM BC DLC region is presented. To derive simple but smart resource allocation strategies, the principle of rate water-filling employing order statistics is introduced. This yields analytical lower bounds on the OFDM DLC region based on orthogonal frequency division multiple access (OFDMA) and ordinal channel state information (CSI). Finally, the schemes are compared to an algorithm using full CSI.
cs/0610067
Language, logic and ontology: uncovering the structure of commonsense knowledge
cs.AI math.LO
The purpose of this paper is twofold: (i) we argue that the structure of commonsense knowledge must be discovered, rather than invented; and (ii) we argue that natural language, which is the best known theory of our (shared) commonsense knowledge, should itself be used as a guide to discovering the structure of commonsense knowledge. In addition to suggesting a systematic method to the discovery of the structure of commonsense knowledge, the method we propose seems to also provide an explanation for a number of phenomena in natural language, such as metaphor, intensionality, and the semantics of nominal compounds. Admittedly, our ultimate goal is quite ambitious, and it is no less than the systematic 'discovery' of a well-typed ontology of commonsense knowledge, and the subsequent formulation of the long-awaited goal of a meaning algebra.
cs/0610074
Collaborative Decoding of Interleaved Reed-Solomon Codes and Concatenated Code Designs
cs.IT math.IT
Interleaved Reed-Solomon codes are applied in numerous data processing, data transmission, and data storage systems. They are generated by interleaving several codewords of ordinary Reed-Solomon codes. Usually, these codewords are decoded independently by classical algebraic decoding methods. However, by collaborative algebraic decoding approaches, such interleaved schemes allow the correction of error patterns beyond half the minimum distance, provided that the errors in the received signal occur in bursts. In this work, collaborative decoding of interleaved Reed-Solomon codes by multi-sequence shift-register synthesis is considered and analyzed. Based on the framework of interleaved Reed-Solomon codes, concatenated code designs are investigated, which are obtained by interleaving several Reed-Solomon codes, and concatenating them with an inner block code.
cs/0610075
On Geometric Algebra representation of Binary Spatter Codes
cs.AI quant-ph
Kanerva's Binary Spatter Codes are reformulated in terms of geometric algebra. The key ingredient of the construction is the representation of XOR binding in terms of geometric product.
cs/0610076
Peano Count Trees (P-Trees) and Rule Association Mining for Gene Expression Profiling of Microarray Data
cs.DS cs.IR q-bio.MN
The greatest challenge in maximizing the use of gene expression data is to develop new computational tools capable of interconnecting and interpreting the results from different organisms and experimental settings. We propose an integrative and comprehensive approach including a super-chip containing data from microarray experiments collected on different species subjected to hypoxic and anoxic stress. A data mining technology called Peano count tree (P-trees) is used to represent genomic data in multidimensions. Each microarray spot is presented as a pixel with its corresponding red/green intensity feature bands. Each bad is stored separately in a reorganized 8-separate (bSQ) file format. Each bSQ is converted to a quadrant base tree structure (P-tree) from which a superchip is represented as expression P-trees (EP-trees) and repression P-trees (RP-trees). The use of association rule mining is proposed to derived to meanigingfully organize signal transduction pathways taking in consideration evolutionary considerations. We argue that the genetic constitution of an organism (K) can be represented by the total number of genes belonging to two groups. The group X constitutes genes (X1,Xn) and they can be represented as 1 or 0 depending on whether the gene was expressed or not. The second group of Y genes (Y1,Yn) is expressed at different levels. These genes have a very high repression, high expression, very repressed or highly repressed. However, many genes of the group Y are specie specific and modulated by the products and combinations of genes of the group X. In this paper, we introduce the dSQ and P-tree technology; the biological implications of association rule mining using X and Y gene groups and some advances in the integration of this information using the BRAIN architecture.
cs/0610077
MIMO Broadcast Channels with Block Diagonalization and Finite Rate Feedback
cs.IT math.IT
Block diagonalization is a linear precoding technique for the multiple antenna broadcast (downlink) channel that involves transmission of multiple data streams to each receiver such that no multi-user interference is experienced at any of the receivers. This low-complexity scheme operates only a few dB away from capacity but does require very accurate channel knowledge at the transmitter, which can be very difficult to obtain in fading scenarios. We consider a limited feedback system where each receiver knows its channel perfectly, but the transmitter is only provided with a finite number of channel feedback bits from each receiver. Using a random vector quantization argument, we quantify the throughput loss due to imperfect channel knowledge as a function of the feedback level. The quality of channel knowledge must improve proportional to the SNR in order to prevent interference-limitations, and we show that scaling the number of feedback bits linearly with the system SNR is sufficient to maintain a bounded rate loss. Finally, we investigate a simple scalar quantization scheme that is seen to achieve the same scaling behavior as vector quantization.
cs/0610079
An Enhanced Covering Lemma for Multiterminal Source Coding
cs.IT math.IT
An enhanced covering lemma for a Markov chain is proved in this paper, and then the distributed source coding problem of correlated general sources with one average distortion criterion under fixed-length coding is investigated. Based on the enhanced lemma, a sufficient and necessary condition for determining the achievability of rate-distortion triples is given.
cs/0610082
Theoretical analysis of network cranback protocols performance
cs.IT math.IT
Suggested the decision of the network cranback protocols performance analyzing problem from Eyal Felstine, Reuven Cohen and Ofer Hadar, " Crankback Prediction in Hierarchical ATM networks", Journal of Network and Systems Management, Vol. 10, No. 3, September 2002. It show that the false alarm probability and probability of successful way crossing can be calculated. The main optimization equations are developed for cranback protocol parameters by using analytical expressions for statistical protocol characteristics.
cs/0610083
Estimation of the traffic in the binary channel for data networks
cs.IT math.IT
It is impossible to provide an effective utilization of communication networks without the analysis of the quantitative characteristics of the traffic in real time. The constant supervision of all channels of the data practically is impracticable because requires transfer of the significant additional information on a network and large resources expenses for devices of the control. Thus, the task on traffic estimation with small expenses in real time is the urgent.
cs/0610091
On the Behavior of Journal Impact Factor Rank-Order Distribution
cs.IR physics.soc-ph
An empirical law for the rank-order behavior of journal impact factors is found. Using an extensive data base on impact factors including journals on Education, Agrosciences, Geosciences, Biosciences and Environ- mental, Chemical, Computer, Engineering, Material, Mathematical, Medical and Physical Sciences we have found extremely good fits out- performing other rank-order models. Some extensions to other areas of knowledge are discussed.
cs/0610093
Semantic results for ontic and epistemic change
cs.LO cs.AI cs.MA
We give some semantic results for an epistemic logic incorporating dynamic operators to describe information changing events. Such events include epistemic changes, where agents become more informed about the non-changing state of the world, and ontic changes, wherein the world changes. The events are executed in information states that are modeled as pointed Kripke models. Our contribution consists of three semantic results. (i) Given two information states, there is an event transforming one into the other. The linguistic correspondent to this is that every consistent formula can be made true in every information state by the execution of an event. (ii) A more technical result is that: every event corresponds to an event in which the postconditions formalizing ontic change are assignments to `true' and `false' only (instead of assignments to arbitrary formulas in the logical language). `Corresponds' means that execution of either event in a given information state results in bisimilar information states. (iii) The third, also technical, result is that every event corresponds to a sequence of events wherein all postconditions are assignments of a single atom only (instead of simultaneous assignments of more than one atom).
cs/0610095
Solving planning domains with polytree causal graphs is NP-complete
cs.AI cs.CC
We show that solving planning domains on binary variables with polytree causal graph is \NP-complete. This is in contrast to a polynomial-time algorithm of Domshlak and Brafman that solves these planning domains for polytree causal graphs of bounded indegree.
cs/0610098
Characterizing Solution Concepts in Games Using Knowledge-Based Programs
cs.GT cs.DC cs.MA
We show how solution concepts in games such as Nash equilibrium, correlated equilibrium, rationalizability, and sequential equilibrium can be given a uniform definition in terms of \emph{knowledge-based programs}. Intuitively, all solution concepts are implementations of two knowledge-based programs, one appropriate for games represented in normal form, the other for games represented in extensive form. These knowledge-based programs can be viewed as embodying rationality. The representation works even if (a) information sets do not capture an agent's knowledge, (b) uncertainty is not represented by probability, or (c) the underlying game is not common knowledge.
cs/0610099
Properties of Codes with the Rank Metric
cs.IT math.IT
In this paper, we study properties of rank metric codes in general and maximum rank distance (MRD) codes in particular. For codes with the rank metric, we first establish Gilbert and sphere-packing bounds, and then obtain the asymptotic forms of these two bounds and the Singleton bound. Based on the asymptotic bounds, we observe that asymptotically Gilbert-Varsharmov bound is exceeded by MRD codes and sphere-packing bound cannot be attained. We also establish bounds on the rank covering radius of maximal codes, and show that all MRD codes are maximal codes and all the MRD codes known so far achieve the maximum rank covering radius.
cs/0610100
A Mobile Transient Internet Architecture
cs.NI cs.IT math.IT
This paper describes a new architecture for transient mobile networks destined to merge existing and future network architectures, communication implementations and protocol operations by introducing a new paradigm to data delivery and identification. The main goal of our research is to enable seamless end-to-end communication between mobile and stationary devices across multiple networks and through multiple communication environments. The architecture establishes a set of infrastructure components and protocols that set the ground for a Persistent Identification Network (PIN). The basis for the operation of PIN is an identification space consisting of unique location independent identifiers similar to the ones implemented in the Handle system. Persistent Identifiers are used to identify and locate Digital Entities which can include devices, services, users and even traffic. The architecture establishes a primary connection independent logical structure that can operate over conventional networks or more advanced peer-to-peer aggregation networks. Communication is based on routing pools and novel protocols for routing data across several abstraction levels of the network, regardless of the end-points' current association and state...
cs/0610102
Quantum communication is possible with pure state
cs.IT math.IT
It is believed that quantum communication is not possible with a pure ensemble of states because quantum entropy of pure state is zero. This is indeed possible due to geometric consequence of entanglement.
cs/0610103
On the Secrecy Capacity of Fading Channels
cs.IT math.IT
We consider the secure transmission of information over an ergodic fading channel in the presence of an eavesdropper. Our eavesdropper can be viewed as the wireless counterpart of Wyner's wiretapper. The secrecy capacity of such a system is characterized under the assumption of asymptotically long coherence intervals. We first consider the full Channel State Information (CSI) case, where the transmitter has access to the channel gains of the legitimate receiver and the eavesdropper. The secrecy capacity under this full CSI assumption serves as an upper bound for the secrecy capacity when only the CSI of the legitimate receiver is known at the transmitter, which is characterized next. In each scenario, the perfect secrecy capacity is obtained along with the optimal power and rate allocation strategies. We then propose a low-complexity on/off power allocation strategy that achieves near-optimal performance with only the main channel CSI. More specifically, this scheme is shown to be asymptotically optimal as the average SNR goes to infinity, and interestingly, is shown to attain the secrecy capacity under the full CSI assumption. Remarkably, our results reveal the positive impact of fading on the secrecy capacity and establish the critical role of rate adaptation, based on the main channel CSI, in facilitating secure communications over slow fading channels.
cs/0610104
ARQ Diversity in Fading Random Access Channels
cs.IT math.IT
A cross-layer optimization approach is adopted for the design of symmetric random access wireless systems. Instead of the traditional collision model, a more realistic physical layer model is considered. Based on this model, an Incremental Redundancy Automatic Repeat reQuest (IR-ARQ) scheme, tailored to jointly combat the effects of collisions, multi-path fading, and additive noise, is developed. The Diversity-Multiplexing-Delay tradeoff (DMDT) of the proposed scheme is analyzed for fully-loaded queues, and compared with that of Gallager tree algorithm for collision resolution and the network-assisted diversity multiple access (NDMA) protocol of Tsatsanis et al.. The fully-loaded queue model is then replaced by one with random arrivals, under which these protocols are compared in terms of the stability region, average delay and diversity gain. Overall, our analytical and numerical results establish the superiority of the proposed IR-ARQ scheme and reveal some important insights. For example, it turns out that the performance is optimized, for a given total throughput, by maximizing the probability that a certain user sends a new packet and minimizing the transmission rate employed by each user.
cs/0610105
How To Break Anonymity of the Netflix Prize Dataset
cs.CR cs.DB
We present a new class of statistical de-anonymization attacks against high-dimensional micro-data, such as individual preferences, recommendations, transaction records and so on. Our techniques are robust to perturbation in the data and tolerate some mistakes in the adversary's background knowledge. We apply our de-anonymization methodology to the Netflix Prize dataset, which contains anonymous movie ratings of 500,000 subscribers of Netflix, the world's largest online movie rental service. We demonstrate that an adversary who knows only a little bit about an individual subscriber can easily identify this subscriber's record in the dataset. Using the Internet Movie Database as the source of background knowledge, we successfully identified the Netflix records of known users, uncovering their apparent political preferences and other potentially sensitive information.
cs/0610106
On the Error Exponents of ARQ Channels with Deadlines
cs.IT math.IT
We consider communication over Automatic Repeat reQuest (ARQ) memoryless channels with deadlines. In particular, an upper bound L is imposed on the maximum number of ARQ transmission rounds. In this setup, it is shown that incremental redundancy ARQ outperforms Forney's memoryless decoding in terms of the achievable error exponents.