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0802.2385
Essential variables and positions in terms
math.GM cs.IT math.IT
The paper deals with $\Sigma-$composition of terms, which allows us to extend the derivation rules in formal deduction of identities. The concept of essential variables and essential positions of terms with respect to a set of identities is a key step in the simplification of the process of formal deduction. $\Sigma-$composition of terms is defined as replacement between $\Sigma$-equal terms. This composition induces $\Sigma R-$deductively closed sets of identities. In analogy to balanced identities we introduce and investigate $\Sigma-$balanced identities for a given set of identities $\Sigma$.
0802.2411
Multiclass Approaches for Support Vector Machine Based Land Cover Classification
cs.NE cs.CV
SVMs were initially developed to perform binary classification; though, applications of binary classification are very limited. Most of the practical applications involve multiclass classification, especially in remote sensing land cover classification. A number of methods have been proposed to implement SVMs to produce multiclass classification. A number of methods to generate multiclass SVMs from binary SVMs have been proposed by researchers and is still a continuing research topic. This paper compares the performance of six multi-class approaches to solve classification problem with remote sensing data in term of classification accuracy and computational cost. One vs. one, one vs. rest, Directed Acyclic Graph (DAG), and Error Corrected Output Coding (ECOC) based multiclass approaches creates many binary classifiers and combines their results to determine the class label of a test pixel. Another catogery of multi class approach modify the binary class objective function and allows simultaneous computation of multiclass classification by solving a single optimisation problem. Results from this study conclude the usefulness of One vs. One multi class approach in term of accuracy and computational cost over other multi class approaches.
0802.2428
Sign Language Tutoring Tool
cs.LG cs.HC
In this project, we have developed a sign language tutor that lets users learn isolated signs by watching recorded videos and by trying the same signs. The system records the user's video and analyses it. If the sign is recognized, both verbal and animated feedback is given to the user. The system is able to recognize complex signs that involve both hand gestures and head movements and expressions. Our performance tests yield a 99% recognition rate on signs involving only manual gestures and 85% recognition rate on signs that involve both manual and non manual components, such as head movement and facial expressions.
0802.2429
Anisotropic selection in cellular genetic algorithms
cs.AI
In this paper we introduce a new selection scheme in cellular genetic algorithms (cGAs). Anisotropic Selection (AS) promotes diversity and allows accurate control of the selective pressure. First we compare this new scheme with the classical rectangular grid shapes solution according to the selective pressure: we can obtain the same takeover time with the two techniques although the spreading of the best individual is different. We then give experimental results that show to what extent AS promotes the emergence of niches that support low coupling and high cohesion. Finally, using a cGA with anisotropic selection on a Quadratic Assignment Problem we show the existence of an anisotropic optimal value for which the best average performance is observed. Further work will focus on the selective pressure self-adjustment ability provided by this new selection scheme.
0802.2451
Capacity of General Discrete Noiseless Channels
cs.IT math.IT
This paper concerns the capacity of the discrete noiseless channel introduced by Shannon. A sufficient condition is given for the capacity to be well-defined. For a general discrete noiseless channel allowing non-integer valued symbol weights, it is shown that the capacity--if well-defined--can be determined from the radius of convergence of its generating function, from the smallest positive pole of its generating function, or from the rightmost real singularity of its complex generating function. A generalisation is given for Pringsheim's Theorem and for the Exponential Growth Formula to generating functions of combinatorial structures with non-integer valued symbol weights.
0802.2476
Theoretical Analysis of the Energy Capture in Strictly Bandlimited Ultra-Wideband Channels
cs.IT math.IT
The frequency selectivity of wireless communication channels can be characterized by the delay spread Ds of the channel impulse response. If the delay spread is small compared to the bandwidth W of the input signal, that is, Ds*W approximately equal to 1, the channel appears to be flat fading. For Ds*W >> 1, the channel appears to be frequency selective, which is usually the case for wideband signals. In the first case, small scale synchronization with a precision much higher than the sampling time T = 1/W is crucial. In this paper, it is shown by analytical means that this is different in the wideband regime. Here synchronization with a precision of T is sufficient and small scale synchronization cannot further increase the captured energy at the receiver. Simulation results show that this effect already occurs for W > 50MHz for the IEEE 802.15.4a channel model.
0802.2574
The minimal set of Ingleton inequalities
cs.IT math.IT
The Ingleton-LP bound is an outer bound for the multicast capacity region, assuming the use of linear network codes. Computation of the bound is performed on a polyhedral cone obtained by taking the intersection of half-spaces induced by the basic (Shannon-type) inequalities and Ingleton inequalities. This paper simplifies the characterization of this cone, by obtaining the unique minimal set of Ingleton inequalities. As a result, the effort required for computation of the Ingleton-LP bound can be greatly reduced.
0802.2587
Order-Optimal Consensus through Randomized Path Averaging
cs.IT cs.NI math.IT math.PR
Gossip algorithms have recently received significant attention, mainly because they constitute simple and robust message-passing schemes for distributed information processing over networks. However for many topologies that are realistic for wireless ad-hoc and sensor networks (like grids and random geometric graphs), the standard nearest-neighbor gossip converges as slowly as flooding ($O(n^2)$ messages). A recently proposed algorithm called geographic gossip improves gossip efficiency by a $\sqrt{n}$ factor, by exploiting geographic information to enable multi-hop long distance communications. In this paper we prove that a variation of geographic gossip that averages along routed paths, improves efficiency by an additional $\sqrt{n}$ factor and is order optimal ($O(n)$ messages) for grids and random geometric graphs. We develop a general technique (travel agency method) based on Markov chain mixing time inequalities, which can give bounds on the performance of randomized message-passing algorithms operating over various graph topologies.
0802.2655
Pure Exploration for Multi-Armed Bandit Problems
math.ST cs.LG stat.TH
We consider the framework of stochastic multi-armed bandit problems and study the possibilities and limitations of forecasters that perform an on-line exploration of the arms. These forecasters are assessed in terms of their simple regret, a regret notion that captures the fact that exploration is only constrained by the number of available rounds (not necessarily known in advance), in contrast to the case when the cumulative regret is considered and when exploitation needs to be performed at the same time. We believe that this performance criterion is suited to situations when the cost of pulling an arm is expressed in terms of resources rather than rewards. We discuss the links between the simple and the cumulative regret. One of the main results in the case of a finite number of arms is a general lower bound on the simple regret of a forecaster in terms of its cumulative regret: the smaller the latter, the larger the former. Keeping this result in mind, we then exhibit upper bounds on the simple regret of some forecasters. The paper ends with a study devoted to continuous-armed bandit problems; we show that the simple regret can be minimized with respect to a family of probability distributions if and only if the cumulative regret can be minimized for it. Based on this equivalence, we are able to prove that the separable metric spaces are exactly the metric spaces on which these regrets can be minimized with respect to the family of all probability distributions with continuous mean-payoff functions.
0802.2666
Distributed Joint Source-Channel Coding for arbitrary memoryless correlated sources and Source coding for Markov correlated sources using LDPC codes
cs.IT math.IT
In this paper, we give a distributed joint source channel coding scheme for arbitrary correlated sources for arbitrary point in the Slepian-Wolf rate region, and arbitrary link capacities using LDPC codes. We consider the Slepian-Wolf setting of two sources and one destination, with one of the sources derived from the other source by some correlation model known at the decoder. Distributed encoding and separate decoding is used for the two sources. We also give a distributed source coding scheme when the source correlation has memory to achieve any point in the Slepian-Wolf rate achievable region. In this setting, we perform separate encoding but joint decoding.
0802.2684
A Simple Distributed Antenna Processing Scheme for Cooperative Diversity
cs.IT math.IT
In this letter the performance of multiple relay channels is analyzed for the situation in which multiple antennas are deployed only at the relays. The simple repetition-coded decodeand- forward protocol with two different antenna processing techniques at the relays is investigated. The antenna combining techniques are maximum ratio combining (MRC) for reception and transmit beamforming (TB) for transmission. It is shown that these distributed antenna combining techniques can exploit the full spatial diversity of the relay channels regardless of the number of relays and antennas at each relay, and offer significant power gain over distributed space-time coding techniques.
0802.2701
Authentication over Noisy Channels
cs.IT cs.CR math.IT
In this work, message authentication over noisy channels is studied. The model developed in this paper is the authentication theory counterpart of Wyner's wiretap channel model. Two types of opponent attacks, namely impersonation attacks and substitution attacks, are investigated for both single message and multiple message authentication scenarios. For each scenario, information theoretic lower and upper bounds on the opponent's success probability are derived. Remarkably, in both scenarios, lower and upper bounds are shown to match, and hence the fundamental limit of message authentication over noisy channels is fully characterized. The opponent's success probability is further shown to be smaller than that derived in the classic authentication model in which the channel is assumed to be noiseless. These results rely on a proposed novel authentication scheme in which key information is used to provide simultaneous protection again both types of attacks.
0802.2703
Optimal Medium Access Protocols for Cognitive Radio Networks
cs.IT cs.NI math.IT
This paper focuses on the design of medium access control protocols for cognitive radio networks. The scenario in which a single cognitive user wishes to opportunistically exploit the availability of empty frequency bands within parts of the radio spectrum having multiple bands is first considered. In this scenario, the availability probability of each channel is unknown a priori to the cognitive user. Hence efficient medium access strategies must strike a balance between exploring (learning) the availability probability of the channels and exploiting the knowledge of the availability probability identified thus far. For this scenario, an optimal medium access strategy is derived and its underlying recursive structure is illustrated via examples. To avoid the prohibitive computational complexity of this optimal strategy, a low complexity asymptotically optimal strategy is developed. Next, the multi-cognitive user scenario is considered and low complexity medium access protocols, which strike an optimal balance between exploration and exploitation in such competitive environments, are developed.
0802.2723
On strongly controllable group codes and mixing group shifts: solvable groups, translation nets, and algorithms
cs.IT math.IT
The branch group of a strongly controllable group code is a shift group. We show that a shift group can be characterized in a very simple way. In addition it is shown that if a strongly controllable group code is labeled with Latin squares, a strongly controllable Latin group code, then the shift group is solvable. Moreover the mathematical structure of a Latin square (as a translation net) and the shift group of a strongly controllable Latin group code are closely related. Thus a strongly controllable Latin group code can be viewed as a natural extension of a Latin square to a sequence space. Lastly we construct shift groups. We show that it is sufficient to construct a simpler group, the state group of a shift group. We give an algorithm to find the state group, and from this it is easy to construct a stronlgy controllable Latin group code.
0802.2773
Stiffness Analysis of 3-d.o.f. Overconstrained Translational Parallel Manipulators
cs.RO physics.class-ph
The paper presents a new stiffness modelling method for overconstrained parallel manipulators, which is applied to 3-d.o.f. translational mechanisms. It is based on a multidimensional lumped-parameter model that replaces the link flexibility by localized 6-d.o.f. virtual springs. In contrast to other works, the method includes a FEA-based link stiffness evaluation and employs a new solution strategy of the kinetostatic equations, which allows computing the stiffness matrix for the overconstrained architectures and for the singular manipulator postures. The advantages of the developed technique are confirmed by application examples, which deal with comparative stiffness analysis of two translational parallel manipulators.
0802.2823
On the decomposition of k-valued rational relations
cs.IT math.IT
We give a new, and hopefully more easily understandable, structural proof of the decomposition of a $k$-valued transducer into $k$ unambiguous functional ones, a result established by A. Weber in 1996. Our construction is based on a lexicographic ordering of computations of automata and on two coverings that can be build by means of this ordering. The complexity of the construction, measured as the number of states of the transducers involved in the decomposition, improves the original one by one exponential. Moreover, this method allows further generalisation that solves the problem of decomposition of rational relations with bounded length-degree, which was left open in Weber's paper.
0802.2826
Efficient Minimization of DFAs with Partial Transition Functions
cs.IT cs.DS math.IT
Let PT-DFA mean a deterministic finite automaton whose transition relation is a partial function. We present an algorithm for minimizing a PT-DFA in $O(m \lg n)$ time and $O(m+n+\alpha)$ memory, where $n$ is the number of states, $m$ is the number of defined transitions, and $\alpha$ is the size of the alphabet. Time consumption does not depend on $\alpha$, because the $\alpha$ term arises from an array that is accessed at random and never initialized. It is not needed, if transitions are in a suitable order in the input. The algorithm uses two instances of an array-based data structure for maintaining a refinable partition. Its operations are all amortized constant time. One instance represents the classical blocks and the other a partition of transitions. Our measurements demonstrate the speed advantage of our algorithm on PT-DFAs over an $O(\alpha n \lg n)$ time, $O(\alpha n)$ memory algorithm.
0802.2839
On Termination for Faulty Channel Machines
cs.IT cs.CC math.IT
A channel machine consists of a finite controller together with several fifo channels; the controller can read messages from the head of a channel and write messages to the tail of a channel. In this paper, we focus on channel machines with insertion errors, i.e., machines in whose channels messages can spontaneously appear. Such devices have been previously introduced in the study of Metric Temporal Logic. We consider the termination problem: are all the computations of a given insertion channel machine finite? We show that this problem has non-elementary, yet primitive recursive complexity.
0802.2842
Weak index versus Borel rank
cs.IT math.IT
We investigate weak recognizability of deterministic languages of infinite trees. We prove that for deterministic languages the Borel hierarchy and the weak index hierarchy coincide. Furthermore, we propose a procedure computing for a deterministic automaton an equivalent minimal index weak automaton with a quadratic number of states. The algorithm works within the time of solving the emptiness problem.
0802.2844
Analytic aspects of the shuffle product
cs.IT math.CO math.IT
There exist very lucid explanations of the combinatorial origins of rational and algebraic functions, in particular with respect to regular and context free languages. In the search to understand how to extend these natural correspondences, we find that the shuffle product models many key aspects of D-finite generating functions, a class which contains algebraic. We consider several different takes on the shuffle product, shuffle closure, and shuffle grammars, and give explicit generating function consequences. In the process, we define a grammar class that models D-finite generating functions.
0802.2856
Convergence Thresholds of Newton's Method for Monotone Polynomial Equations
cs.DS cs.IT cs.NA math.IT
Monotone systems of polynomial equations (MSPEs) are systems of fixed-point equations $X_1 = f_1(X_1, ..., X_n),$ $..., X_n = f_n(X_1, ..., X_n)$ where each $f_i$ is a polynomial with positive real coefficients. The question of computing the least non-negative solution of a given MSPE $\vec X = \vec f(\vec X)$ arises naturally in the analysis of stochastic models such as stochastic context-free grammars, probabilistic pushdown automata, and back-button processes. Etessami and Yannakakis have recently adapted Newton's iterative method to MSPEs. In a previous paper we have proved the existence of a threshold $k_{\vec f}$ for strongly connected MSPEs, such that after $k_{\vec f}$ iterations of Newton's method each new iteration computes at least 1 new bit of the solution. However, the proof was purely existential. In this paper we give an upper bound for $k_{\vec f}$ as a function of the minimal component of the least fixed-point $\mu\vec f$ of $\vec f(\vec X)$. Using this result we show that $k_{\vec f}$ is at most single exponential resp. linear for strongly connected MSPEs derived from probabilistic pushdown automata resp. from back-button processes. Further, we prove the existence of a threshold for arbitrary MSPEs after which each new iteration computes at least $1/w2^h$ new bits of the solution, where $w$ and $h$ are the width and height of the DAG of strongly connected components.
0802.2975
Hard Fairness Versus Proportional Fairness in Wireless Communications: The Multiple-Cell Case
cs.IT math.IT
We consider the uplink of a cellular communication system with $K$ users per cell and infinite base stations equally spaced on a line. The system is conventional, i.e., it does not make use of joint cell-site processing. A hard fairness (HF) system serves all users with the same rate in any channel state. In contrast, a system based on proportional fairness serves the users with variable instantaneous rates depending on their channel state. We compare these two options in terms of the system spectral efficiency \textsf{C} (bit/s/Hz) versus $E_b/N_0$. Proportional fair scheduling (PFS) performs generally better than the more restrictive HF system in the regime of low to moderate SNR, but for high SNR an optimized HF system achieves throughput comparable to that of PFS system for finite $K$. The hard-fairness system is interference limited. We characterize this limit and validate a commonly used simplified model that treats outer cell interference power as proportional to the in-cell total power and we analytically characterize the proportionality constant. In contrast, the spectral efficiency of PFS can grow unbounded for $K \to \infty$ thanks to the multiuser diversity effect. We also show that partial frequency/time reuse can mitigate the throughput penalty of the HF system, especially at high SNR.
0802.3110
An entropic view of Pickands' theorem
cs.IT math.IT
It is shown that distributions arising in Renyi-Tsallis maximum entropy setting are related to the Generalized Pareto Distributions (GPD) that are widely used for modeling the tails of distributions. The relevance of such modelization, as well as the ubiquity of GPD in practical situations follows from Balkema-De Haan-Pickands theorem on the distribution of excesses (over a high threshold). We provide an entropic view of this result, by showing that the distribution of a suitably normalized excess variable converges to the solution of a maximum Tsallis entropy, which is the GPD. This highlights the relevance of the so-called Tsallis distributions in many applications as well as some relevance to the use of the corresponding entropy.
0802.3137
Design and Implementation of Aggregate Functions in the DLV System
cs.AI cs.LO
Disjunctive Logic Programming (DLP) is a very expressive formalism: it allows for expressing every property of finite structures that is decidable in the complexity class SigmaP2 (= NP^NP). Despite this high expressiveness, there are some simple properties, often arising in real-world applications, which cannot be encoded in a simple and natural manner. Especially properties that require the use of arithmetic operators (like sum, times, or count) on a set or multiset of elements, which satisfy some conditions, cannot be naturally expressed in classic DLP. To overcome this deficiency, we extend DLP by aggregate functions in a conservative way. In particular, we avoid the introduction of constructs with disputed semantics, by requiring aggregates to be stratified. We formally define the semantics of the extended language (called DLP^A), and illustrate how it can be profitably used for representing knowledge. Furthermore, we analyze the computational complexity of DLP^A, showing that the addition of aggregates does not bring a higher cost in that respect. Finally, we provide an implementation of DLP^A in DLV -- a state-of-the-art DLP system -- and report on experiments which confirm the usefulness of the proposed extension also for the efficiency of computation.
0802.3235
Characterization of the convergence of stationary Fokker-Planck learning
cs.NE cond-mat.dis-nn cs.AI
The convergence properties of the stationary Fokker-Planck algorithm for the estimation of the asymptotic density of stochastic search processes is studied. Theoretical and empirical arguments for the characterization of convergence of the estimation in the case of separable and nonseparable nonlinear optimization problems are given. Some implications of the convergence of stationary Fokker-Planck learning for the inference of parameters in artificial neural network models are outlined.
0802.3253
On the Capacity and Design of Limited Feedback Multiuser MIMO Uplinks
cs.IT cs.MM math.IT
The theory of multiple-input multiple-output (MIMO) technology has been well-developed to increase fading channel capacity over single-input single-output (SISO) systems. This capacity gain can often be leveraged by utilizing channel state information at the transmitter and the receiver. Users make use of this channel state information for transmit signal adaptation. In this correspondence, we derive the capacity region for the MIMO multiple access channel (MIMO MAC) when partial channel state information is available at the transmitters, where we assume a synchronous MIMO multiuser uplink. The partial channel state information feedback has a cardinality constraint and is fed back from the basestation to the users using a limited rate feedback channel. Using this feedback information, we propose a finite codebook design method to maximize sum-rate. In this correspondence, the codebook is a set of transmit signal covariance matrices. We also derive the capacity region and codebook design methods in the case that the covariance matrix is rank-one (i.e., beamforming). This is motivated by the fact that beamforming is optimal in certain conditions. The simulation results show that when the number of feedback bits increases, the capacity also increases. Even with a small number of feedback bits, the performance of the proposed system is close to an optimal solution with the full feedback.
0802.3285
Some Aspects of Testing Process for Transport Streams in Digital Video Broadcasting
cs.CV cs.MM
This paper presents some aspects related to the DVB (Digital Video Broadcasting) investigation. The basic aspects of DVB are presented, with an emphasis on DVB-T version of standard. The main purpose of this research is to analyze the way that the transmission of the transport streams is realized in case of the Terrestrial Digital Video Broadcasting (DVB-T). To accomplish this, first, Digital Video Broadcasting standard is presented, and then the main aspects of DVB testing and analysis of the transport streams are investigated. The paper presents also the results obtained using two programs designed for DVB analysis: Mosalina and TSA.
0802.3288
Implementing a Test Strategy for an Advanced Video Acquisition and Processing Architecture
cs.CV cs.MM
This paper presents some aspects related to test process of an advanced video system used in remote IP surveillance. The system is based on a Pentium compatible architecture using the industrial standard PC104+. First the overall architecture of the system is presented, involving both hardware or software aspects. The acquisition board which is developed in a special, nonstandard architecture, is also briefly presented. The main purpose of this research was to set a coherent set of procedures in order to test all the aspects of the video acquisition board. To accomplish this, it was necessary to set-up a procedure in two steps: stand alone video board test (functional test) and an in-system test procedure verifying the compatibility with both OS: Linux and Windows. The paper presents also the results obtained using this procedure.
0802.3293
Use of Rapid Probabilistic Argumentation for Ranking on Large Complex Networks
cs.AI cs.IR
We introduce a family of novel ranking algorithms called ERank which run in linear/near linear time and build on explicitly modeling a network as uncertain evidence. The model uses Probabilistic Argumentation Systems (PAS) which are a combination of probability theory and propositional logic, and also a special case of Dempster-Shafer Theory of Evidence. ERank rapidly generates approximate results for the NP-complete problem involved enabling the use of the technique in large networks. We use a previously introduced PAS model for citation networks generalizing it for all networks. We propose a statistical test to be used for comparing the performances of different ranking algorithms based on a clustering validity test. Our experimentation using this test on a real-world network shows ERank to have the best performance in comparison to well-known algorithms including PageRank, closeness, and betweenness.
0802.3401
On the Structure of the Capacity Region of Asynchronous Memoryless Multiple-Access Channels
cs.IT math.IT
The asynchronous capacity region of memoryless multiple-access channels is the union of certain polytopes. It is well-known that vertices of such polytopes may be approached via a technique called successive decoding. It is also known that an extension of successive decoding applies to the dominant face of such polytopes. The extension consists of forming groups of users in such a way that users within a group are decoded jointly whereas groups are decoded successively. This paper goes one step further. It is shown that successive decoding extends to every face of the above mentioned polytopes. The group composition as well as the decoding order for all rates on a face of interest are obtained from a label assigned to that face. From the label one can extract a number of structural properties, such as the dimension of the corresponding face and whether or not two faces intersect. Expressions for the the number of faces of any given dimension are also derived from the labels.
0802.3414
A Universal In-Place Reconfiguration Algorithm for Sliding Cube-Shaped Robots in a Quadratic Number of Moves
cs.CG cs.MA cs.RO
In the modular robot reconfiguration problem, we are given $n$ cube-shaped modules (or robots) as well as two configurations, i.e., placements of the $n$ modules so that their union is face-connected. The goal is to find a sequence of moves that reconfigures the modules from one configuration to the other using "sliding moves," in which a module slides over the face or edge of a neighboring module, maintaining connectivity of the configuration at all times. For many years it has been known that certain module configurations in this model require at least $\Omega(n^2)$ moves to reconfigure between them. In this paper, we introduce the first universal reconfiguration algorithm -- i.e., we show that any $n$-module configuration can reconfigure itself into any specified $n$-module configuration using just sliding moves. Our algorithm achieves reconfiguration in $O(n^2)$ moves, making it asymptotically tight. We also present a variation that reconfigures in-place, it ensures that throughout the reconfiguration process, all modules, except for one, will be contained in the union of the bounding boxes of the start and end configuration.
0802.3419
Randomized Frameproof Codes: Fingerprinting Plus Validation Minus Tracing
cs.IT cs.CR math.IT
We propose randomized frameproof codes for content protection, which arise by studying a variation of the Boneh-Shaw fingerprinting problem. In the modified system, whenever a user tries to access his fingerprinted copy, the fingerprint is submitted to a validation algorithm to verify that it is indeed permissible before the content can be executed. We show an improvement in the achievable rates compared to deterministic frameproof codes and traditional fingerprinting codes. For coalitions of an arbitrary fixed size, we construct randomized frameproof codes which have an $O(n^2)$ complexity validation algorithm and probability of error $\exp(-\Omega(n)),$ where $n$ denotes the length of the fingerprints. Finally, we present a connection between linear frameproof codes and minimal vectors for size-2 coalitions.
0802.3429
Quasi-Large Sparse-Sequence CDMA: Approach to Single-User Bound by Linearly-Complex LAS Detectors
cs.IT math.IT
We have proposed a quasi-large random-sequence (QLRS) CDMA where K users access a point through a common channel with spectral spreading factor N. Each bit is extended by a temporal spreading factor B and hopped on a BN-chip random sequence that is spread in time and frequency. Each user multiplexes and transmits B extended bits and the total channel load is alpha = K/N bits/s/Hz. The linearly-complex LAS detectors detect the transmitted bits. We have obtained that as B tends to infinity, if alpha < 1/2 - 1/(4ln2), each transmitted bit achieves the single-bit bound in BER in high SNR regime as if there was no interference bit. In simulation, when bit number BK >= 500, each bit can approach the single-bit bound for alpha as high as 1 bit/s/Hz. In this paper, we further propose the quasi-large sparse-sequence (QLSS) CDMA by replacing the dense sequence in QLRS-CDMA with sparse sequence. Simulation results show that when the nonzero chips are as few as 16, the BER is already near that of QLRS-CDMA while the complexity is significantly reduced due to sequence sparsity.
0802.3430
A Class of Nonbinary Codes and Their Weight Distribution
cs.IT math.IT
In this paper, for an even integer $n\geq 4$ and any positive integer $k$ with ${\rm gcd}(n/2,k)={\rm gcd}(n/2-k,2k)=d$ being odd, a class of $p$-ary codes $\mathcal{C}^k$ is defined and their weight distribution is completely determined, where $p$ is an odd prime. As an application, a class of nonbinary sequence families is constructed from these codes, and the correlation distribution is also determined.
0802.3437
On Cusick-Cheon's Conjecture About Balanced Boolean Functions in the Cosets of the Binary Reed-Muller Code
cs.IT math.IT
It is proved an amplification of Cusick-Cheon's conjecture on balanced Boolean functions in the cosets of the binary Reed-Muller code RM(k,m) of order k and length 2^m, in the cases where k = 1 or k >= (m-1)/2.
0802.3448
Sketch-Based Estimation of Subpopulation-Weight
cs.DB cs.DS cs.NI cs.PF
Summaries of massive data sets support approximate query processing over the original data. A basic aggregate over a set of records is the weight of subpopulations specified as a predicate over records' attributes. Bottom-k sketches are a powerful summarization format of weighted items that includes priority sampling and the classic weighted sampling without replacement. They can be computed efficiently for many representations of the data including distributed databases and data streams. We derive novel unbiased estimators and efficient confidence bounds for subpopulation weight. Our estimators and bounds are tailored by distinguishing between applications (such as data streams) where the total weight of the sketched set can be computed by the summarization algorithm without a significant use of additional resources, and applications (such as sketches of network neighborhoods) where this is not the case. Our rigorous derivations are based on clever applications of the Horvitz-Thompson estimator, and are complemented by efficient computational methods. We demonstrate their benefit on a wide range of Pareto distributions.
0802.3490
On capacity of wireless ad hoc networks with MIMO MMSE receivers
cs.NI cs.IT math.IT
Widely adopted at home, business places, and hot spots, wireless ad-hoc networks are expected to provide broadband services parallel to their wired counterparts in near future. To address this need, MIMO techniques, which are capable of offering several-fold increase in capacity, hold significant promise. Most previous work on capacity analysis of ad-hoc networks is based on an implicit assumption that each node has only one antenna. Core to the analysis therein is the characterization of a geometric area, referred to as the exclusion region, which quantizes the amount of spatial resource occupied by a link. When multiple antennas are deployed at each node, however, multiple links can transmit in the vicinity of each other simultaneously, as interference can now be suppressed by spatial signal processing. As such, a link no longer exclusively occupies a geometric area, making the concept of "exclusion region" not applicable any more. In this paper, we investigate link-layer throughput capacity of MIMO ad-hoc networks. In contrast to previous work, the amount of spatial resource occupied by each link is characterized by the actual interference it imposes on other links. To calculate the link-layer capacity, we first derive the probability distribution of post-detection SINR at a receiver. The result is then used to calculate the number of active links and the corresponding data rates that can be sustained within an area. Our analysis will serve as a guideline for the design of medium access protocols for MIMO ad-hoc networks. To the best of knowledge, this paper is the first attempt to characterize the capacity of MIMO ad-hoc networks by considering the actual PHY-layer signal and interference model.
0802.3495
Gaussian Interference Networks: Sum Capacity in the Low Interference Regime and New Outer Bounds on the Capacity Region
cs.IT math.IT
Establishing the capacity region of a Gaussian interference network is an open problem in information theory. Recent progress on this problem has led to the characterization of the capacity region of a general two user Gaussian interference channel within one bit. In this paper, we develop new, improved outer bounds on the capacity region. Using these bounds, we show that treating interference as noise achieves the sum capacity of the two user Gaussian interference channel in a low interference regime, where the interference parameters are below certain thresholds. We then generalize our techniques and results to Gaussian interference networks with more than two users. In particular, we demonstrate that the total interference threshold, below which treating interference as noise achieves the sum capacity, increases with the number of users.
0802.3522
Time Warp Edit Distance
cs.IR
This technical report details a family of time warp distances on the set of discrete time series. This family is constructed as an editing distance whose elementary operations apply on linear segments. A specific parameter allows controlling the stiffness of the elastic matching. It is well suited for the processing of event data for which each data sample is associated with a timestamp, not necessarily obtained according to a constant sampling rate. Some properties verified by these distances are proposed and proved in this report.
0802.3528
Wavelet and Curvelet Moments for Image Classification: Application to Aggregate Mixture Grading
cs.CV
We show the potential for classifying images of mixtures of aggregate, based themselves on varying, albeit well-defined, sizes and shapes, in order to provide a far more effective approach compared to the classification of individual sizes and shapes. While a dominant (additive, stationary) Gaussian noise component in image data will ensure that wavelet coefficients are of Gaussian distribution, long tailed distributions (symptomatic, for example, of extreme values) may well hold in practice for wavelet coefficients. Energy (2nd order moment) has often been used for image characterization for image content-based retrieval, and higher order moments may be important also, not least for capturing long tailed distributional behavior. In this work, we assess 2nd, 3rd and 4th order moments of multiresolution transform -- wavelet and curvelet transform -- coefficients as features. As analysis methodology, taking account of image types, multiresolution transforms, and moments of coefficients in the scales or bands, we use correspondence analysis as well as k-nearest neighbors supervised classification.
0802.3535
Approximate Capacity of Gaussian Relay Networks
cs.IT math.IT
We present an achievable rate for general Gaussian relay networks. We show that the achievable rate is within a constant number of bits from the information-theoretic cut-set upper bound on the capacity of these networks. This constant depends on the topology of the network, but not the values of the channel gains. Therefore, we uniformly characterize the capacity of Gaussian relay networks within a constant number of bits, for all channel parameters.
0802.3563
Distributed Sensor Localization in Random Environments using Minimal Number of Anchor Nodes
cs.IT math.IT
The paper develops DILOC, a \emph{distributive}, \emph{iterative} algorithm that locates M sensors in $\mathbb{R}^m, m\geq 1$, with respect to a minimal number of m+1 anchors with known locations. The sensors exchange data with their neighbors only; no centralized data processing or communication occurs, nor is there centralized knowledge about the sensors' locations. DILOC uses the barycentric coordinates of a sensor with respect to its neighbors that are computed using the Cayley-Menger determinants. These are the determinants of matrices of inter-sensor distances. We show convergence of DILOC by associating with it an absorbing Markov chain whose absorbing states are the anchors. We introduce a stochastic approximation version extending DILOC to random environments when the knowledge about the intercommunications among sensors and the inter-sensor distances are noisy, and the communication links among neighbors fail at random times. We show a.s. convergence of the modified DILOC and characterize the error between the final estimates and the true values of the sensors' locations. Numerical studies illustrate DILOC under a variety of deterministic and random operating conditions.
0802.3570
Asymptotic Behaviour of Random Vandermonde Matrices with Entries on the Unit Circle
cs.IT math.IT
Analytical methods for finding moments of random Vandermonde matrices with entries on the unit circle are developed. Vandermonde Matrices play an important role in signal processing and wireless applications such as direction of arrival estimation, precoding, and sparse sampling theory, just to name a few. Within this framework, we extend classical freeness results on random matrices with independent, identically distributed (i.i.d.) entries and show that Vandermonde structured matrices can be treated in the same vein with different tools. We focus on various types of matrices, such as Vandermonde matrices with and without uniform phase distributions, as well as generalized Vandermonde matrices. In each case, we provide explicit expressions of the moments of the associated Gram matrix, as well as more advanced models involving the Vandermonde matrix. Comparisons with classical i.i.d. random matrix theory are provided, and deconvolution results are discussed. We review some applications of the results to the fields of signal processing and wireless communications.
0802.3572
Random Vandermonde Matrices-Part II: Applications
cs.IT math.IT
This paper has been withdrawn by the authors, since it has been merged with Part I (ID 0802.3570)
0802.3582
Neural Networks and Database Systems
cs.DB cs.NE
Object-oriented database systems proved very valuable at handling and administrating complex objects. In the following guidelines for embedding neural networks into such systems are presented. It is our goal to treat networks as normal data in the database system. From the logical point of view, a neural network is a complex data value and can be stored as a normal data object. It is generally accepted that rule-based reasoning will play an important role in future database applications. The knowledge base consists of facts and rules, which are both stored and handled by the underlying database system. Neural networks can be seen as representation of intensional knowledge of intelligent database systems. So they are part of a rule based knowledge pool and can be used like conventional rules. The user has a unified view about his knowledge base regardless of the origin of the unique rules.
0802.3597
Processing Information in Quantum Decision Theory
physics.soc-ph cs.AI quant-ph
A survey is given summarizing the state of the art of describing information processing in Quantum Decision Theory, which has been recently advanced as a novel variant of decision making, based on the mathematical theory of separable Hilbert spaces. This mathematical structure captures the effect of superposition of composite prospects, including many incorporated intended actions. The theory characterizes entangled decision making, non-commutativity of subsequent decisions, and intention interference. The self-consistent procedure of decision making, in the frame of the quantum decision theory, takes into account both the available objective information as well as subjective contextual effects. This quantum approach avoids any paradox typical of classical decision theory. Conditional maximization of entropy, equivalent to the minimization of an information functional, makes it possible to connect the quantum and classical decision theories, showing that the latter is the limit of the former under vanishing interference terms.
0802.3611
Power Allocation for Fading Channels with Peak-to-Average Power Constraints
cs.IT math.IT
Power allocation with peak-to-average power ratio constraints is investigated for transmission over Nakagami-m fading channels with arbitrary input distributions. In the case of delay-limited block-fading channels, we find the solution to the minimum outage power allocation scheme with peak-to-average power constraints and arbitrary input distributions, and show that the signal-to-noise ratio exponent for any finite peak-to-average power ratio is the same as that of the peak-power limited problem, resulting in an error floor. In the case of the ergodic fully-interleaved channel, we find the power allocation rule that yields the maximal information rate for an arbitrary input distribution and show that capacities with peak-to-average power ratio constraints, even for small ratios, are very close to capacities without peak-power restrictions.
0802.3746
Information Hiding Techniques: A Tutorial Review
cs.CR cs.IR
The purpose of this tutorial is to present an overview of various information hiding techniques. A brief history of steganography is provided along with techniques that were used to hide information. Text, image and audio based information hiding techniques are discussed. This paper also provides a basic introduction to digital watermarking.
0802.3784
Pattern-Oriented Analysis and Design (POAD) Theory
cs.SE cs.IT math.IT
Pattern-Oriented Analysis and Design (POAD) is the practice of building complex software by applying proven designs to specific problem domains. Although a great deal of research and practice has been devoted to formalizing existing design patterns and discovering new ones, there has been relatively little research into methods for combining these patterns into software applications. This is partly because the creation of complex software applications is so expensive. This paper proposes a mathematical model of POAD that may allow future research in pattern-oriented techniques to be performed using less expensive formal techniques rather than expensive, complex software development.
0802.3789
Knowledge Technologies
cs.CY cs.AI cs.LG cs.SE
Several technologies are emerging that provide new ways to capture, store, present and use knowledge. This book is the first to provide a comprehensive introduction to five of the most important of these technologies: Knowledge Engineering, Knowledge Based Engineering, Knowledge Webs, Ontologies and Semantic Webs. For each of these, answers are given to a number of key questions (What is it? How does it operate? How is a system developed? What can it be used for? What tools are available? What are the main issues?). The book is aimed at students, researchers and practitioners interested in Knowledge Management, Artificial Intelligence, Design Engineering and Web Technologies. During the 1990s, Nick worked at the University of Nottingham on the application of AI techniques to knowledge management and on various knowledge acquisition projects to develop expert systems for military applications. In 1999, he joined Epistemics where he worked on numerous knowledge projects and helped establish knowledge management programmes at large organisations in the engineering, technology and legal sectors. He is author of the book "Knowledge Acquisition in Practice", which describes a step-by-step procedure for acquiring and implementing expertise. He maintains strong links with leading research organisations working on knowledge technologies, such as knowledge-based engineering, ontologies and semantic technologies.
0802.3851
Joint Source Channel Coding with Side Information Using Hybrid Digital Analog Codes
cs.IT math.IT
We study the joint source channel coding problem of transmitting an analog source over a Gaussian channel in two cases - (i) the presence of interference known only to the transmitter and (ii) in the presence of side information known only to the receiver. We introduce hybrid digital analog forms of the Costa and Wyner-Ziv coding schemes. Our schemes are based on random coding arguments and are different from the nested lattice schemes by Kochman and Zamir that use dithered quantization. We also discuss superimposed digital and analog schemes for the above problems which show that there are infinitely many schemes for achieving the optimal distortion for these problems. This provides an extension of the schemes by Bross et al to the interference/side information case. We then discuss applications of the hybrid digital analog schemes for transmitting under a channel signal-to-noise ratio mismatch and for broadcasting a Gaussian source with bandwidth compression.
0802.3875
Are complex systems hard to evolve?
cs.NE
Evolutionary complexity is here measured by the number of trials/evaluations needed for evolving a logical gate in a non-linear medium. Behavioural complexity of the gates evolved is characterised in terms of cellular automata behaviour. We speculate that hierarchies of behavioural and evolutionary complexities are isomorphic up to some degree, subject to substrate specificity of evolution and the spectrum of evolution parameters.
0802.3950
Belief Propagation and Loop Series on Planar Graphs
cond-mat.stat-mech cs.AI cs.IT math.IT
We discuss a generic model of Bayesian inference with binary variables defined on edges of a planar graph. The Loop Calculus approach of [1, 2] is used to evaluate the resulting series expansion for the partition function. We show that, for planar graphs, truncating the series at single-connected loops reduces, via a map reminiscent of the Fisher transformation [3], to evaluating the partition function of the dimer matching model on an auxiliary planar graph. Thus, the truncated series can be easily re-summed, using the Pfaffian formula of Kasteleyn [4]. This allows to identify a big class of computationally tractable planar models reducible to a dimer model via the Belief Propagation (gauge) transformation. The Pfaffian representation can also be extended to the full Loop Series, in which case the expansion becomes a sum of Pfaffian contributions, each associated with dimer matchings on an extension to a subgraph of the original graph. Algorithmic consequences of the Pfaffian representation, as well as relations to quantum and non-planar models, are discussed.
0802.3992
Polynomial Filtering for Fast Convergence in Distributed Consensus
cs.IT math.IT
In the past few years, the problem of distributed consensus has received a lot of attention, particularly in the framework of ad hoc sensor networks. Most methods proposed in the literature address the consensus averaging problem by distributed linear iterative algorithms, with asymptotic convergence of the consensus solution. The convergence rate of such distributed algorithms typically depends on the network topology and the weights given to the edges between neighboring sensors, as described by the network matrix. In this paper, we propose to accelerate the convergence rate for given network matrices by the use of polynomial filtering algorithms. The main idea of the proposed methodology is to apply a polynomial filter on the network matrix that will shape its spectrum in order to increase the convergence rate. Such an algorithm is equivalent to periodic updates in each of the sensors by aggregating a few of its previous estimates. We formulate the computation of the coefficients of the optimal polynomial as a semi-definite program that can be efficiently and globally solved for both static and dynamic network topologies. We finally provide simulation results that demonstrate the effectiveness of the proposed solutions in accelerating the convergence of distributed consensus averaging problems.
0802.4002
Sensing Danger: Innate Immunology for Intrusion Detection
cs.NE cs.CR
The immune system provides an ideal metaphor for anomaly detection in general and computer security in particular. Based on this idea, artificial immune systems have been used for a number of years for intrusion detection, unfortunately so far with little success. However, these previous systems were largely based on immunological theory from the 1970s and 1980s and over the last decade our understanding of immunological processes has vastly improved. In this paper we present two new immune inspired algorithms based on the latest immunological discoveries, such as the behaviour of Dendritic Cells. The resultant algorithms are applied to real world intrusion problems and show encouraging results. Overall, we believe there is a bright future for these next generation artificial immune algorithms.
0802.4010
Brain architecture: A design for natural computation
q-bio.NC cs.AI cs.NE physics.soc-ph
Fifty years ago, John von Neumann compared the architecture of the brain with that of computers that he invented and which is still in use today. In those days, the organisation of computers was based on concepts of brain organisation. Here, we give an update on current results on the global organisation of neural systems. For neural systems, we outline how the spatial and topological architecture of neuronal and cortical networks facilitates robustness against failures, fast processing, and balanced network activation. Finally, we discuss mechanisms of self-organization for such architectures. After all, the organization of the brain might again inspire computer architecture.
0802.4079
Families of LDPC Codes Derived from Nonprimitive BCH Codes and Cyclotomic Cosets
cs.IT math.IT
Low-density parity check (LDPC) codes are an important class of codes with many applications. Two algebraic methods for constructing regular LDPC codes are derived -- one based on nonprimitive narrow-sense BCH codes and the other directly based on cyclotomic cosets. The constructed codes have high rates and are free of cycles of length four; consequently, they can be decoded using standard iterative decoding algorithms. The exact dimension and bounds for the minimum distance and stopping distance are derived. These constructed codes can be used to derive quantum error-correcting codes.
0802.4089
An algorithmic complexity interpretation of Lin's third law of information theory
cs.CC cs.IT math.IT
Instead of static entropy we assert that the Kolmogorov complexity of a static structure such as a solid is the proper measure of disorder (or chaoticity). A static structure in a surrounding perfectly-random universe acts as an interfering entity which introduces local disruption in randomness. This is modeled by a selection rule $R$ which selects a subsequence of the random input sequence that hits the structure. Through the inequality that relates stochasticity and chaoticity of random binary sequences we maintain that Lin's notion of stability corresponds to the stability of the frequency of 1s in the selected subsequence. This explains why more complex static structures are less stable. Lin's third law is represented as the inevitable change that static structure undergo towards conforming to the universe's perfect randomness.
0802.4101
New bounds on classical and quantum one-way communication complexity
cs.IT cs.DC math.IT
In this paper we provide new bounds on classical and quantum distributional communication complexity in the two-party, one-way model of communication. In the classical model, our bound extends the well known upper bound of Kremer, Nisan and Ron to include non-product distributions. We show that for a boolean function f:X x Y -> {0,1} and a non-product distribution mu on X x Y and epsilon in (0,1/2) constant: D_{epsilon}^{1, mu}(f)= O((I(X:Y)+1) vc(f)), where D_{epsilon}^{1, mu}(f) represents the one-way distributional communication complexity of f with error at most epsilon under mu; vc(f) represents the Vapnik-Chervonenkis dimension of f and I(X:Y) represents the mutual information, under mu, between the random inputs of the two parties. For a non-boolean function f:X x Y ->[k], we show a similar upper bound on D_{epsilon}^{1, mu}(f) in terms of k, I(X:Y) and the pseudo-dimension of f' = f/k. In the quantum one-way model we provide a lower bound on the distributional communication complexity, under product distributions, of a function f, in terms the well studied complexity measure of f referred to as the rectangle bound or the corruption bound of f . We show for a non-boolean total function f : X x Y -> Z and a product distribution mu on XxY, Q_{epsilon^3/8}^{1, mu}(f) = Omega(rec_ epsilon^{1, mu}(f)), where Q_{epsilon^3/8}^{1, mu}(f) represents the quantum one-way distributional communication complexity of f with error at most epsilon^3/8 under mu and rec_ epsilon^{1, mu}(f) represents the one-way rectangle bound of f with error at most epsilon under mu . Similarly for a non-boolean partial function f:XxY -> Z U {*} and a product distribution mu on X x Y, we show, Q_{epsilon^6/(2 x 15^4)}^{1, mu}(f) = Omega(rec_ epsilon^{1, mu}(f)).
0802.4112
Hubs in Languages: Scale Free Networks of Synonyms
physics.soc-ph cs.CL physics.data-an
Natural languages are described in this paper in terms of networks of synonyms: a word is identified with a node, and synonyms are connected by undirected links. Our statistical analysis of the network of synonyms in Polish language showed it is scale-free; similar to what is known for English. The statistical properties of the networks are also similar. Thus, the statistical aspects of the networks are good candidates for culture independent elements of human language. We hypothesize that optimization for robustness and efficiency is responsible for this universality. Despite the statistical similarity, there is no one-to-one mapping between networks of these two languages. Although many hubs in Polish are translated into similarly highly connected hubs in English, there are also hubs specific to one of these languages only: a single word in one language is equivalent to many different and disconnected words in the other, in accordance with the Whorf hypothesis about language relativity. Identifying language-specific hubs is vitally important for automatic translation, and for understanding contextual, culturally related messages that are frequently missed or twisted in a naive, literary translation.
0802.4126
Hospital Case Cost Estimates Modelling - Algorithm Comparison
cs.CE cs.DB
Ontario (Canada) Health System stakeholders support the idea and necessity of the integrated source of data that would include both clinical (e.g. diagnosis, intervention, length of stay, case mix group) and financial (e.g. cost per weighted case, cost per diem) characteristics of the Ontario healthcare system activities at the patient-specific level. At present, the actual patient-level case costs in the explicit form are not available in the financial databases for all hospitals. The goal of this research effort is to develop financial models that will assign each clinical case in the patient-specific data warehouse a dollar value, representing the cost incurred by the Ontario health care facility which treated the patient. Five mathematical models have been developed and verified using real dataset. All models can be classified into two groups based on their underlying method: 1. Models based on using relative intensity weights of the cases, and 2. Models based on using cost per diem.
0802.4130
Wideband Spectrum Sensing in Cognitive Radio Networks
cs.IT math.IT
Spectrum sensing is an essential enabling functionality for cognitive radio networks to detect spectrum holes and opportunistically use the under-utilized frequency bands without causing harmful interference to legacy networks. This paper introduces a novel wideband spectrum sensing technique, called multiband joint detection, which jointly detects the signal energy levels over multiple frequency bands rather than consider one band at a time. The proposed strategy is efficient in improving the dynamic spectrum utilization and reducing interference to the primary users. The spectrum sensing problem is formulated as a class of optimization problems in interference limited cognitive radio networks. By exploiting the hidden convexity in the seemingly non-convex problem formulations, optimal solutions for multiband joint detection are obtained under practical conditions. Simulation results show that the proposed spectrum sensing schemes can considerably improve the system performance. This paper establishes important principles for the design of wideband spectrum sensing algorithms in cognitive radio networks.
0802.4198
Some properties of the Ukrainian writing system
cs.CL
We investigate the grapheme-phoneme relation in Ukrainian and some properties of the Ukrainian version of the Cyrillic alphabet.
0802.4215
Equilibrium (Zipf) and Dynamic (Grasseberg-Procaccia) method based analyses of human texts. A comparison of natural (english) and artificial (esperanto) languages
physics.soc-ph cs.CL physics.data-an
A comparison of two english texts from Lewis Carroll, one (Alice in wonderland), also translated into esperanto, the other (Through a looking glass) are discussed in order to observe whether natural and artificial languages significantly differ from each other. One dimensional time series like signals are constructed using only word frequencies (FTS) or word lengths (LTS). The data is studied through (i) a Zipf method for sorting out correlations in the FTS and (ii) a Grassberger-Procaccia (GP) technique based method for finding correlations in LTS. Features are compared : different power laws are observed with characteristic exponents for the ranking properties, and the {\it phase space attractor dimensionality}. The Zipf exponent can take values much less than unity ($ca.$ 0.50 or 0.30) depending on how a sentence is defined. This non-universality is conjectured to be a measure of the author $style$. Moreover the attractor dimension $r$ is a simple function of the so called phase space dimension $n$, i.e., $r = n^{\lambda}$, with $\lambda = 0.79$. Such an exponent should also conjecture to be a measure of the author $creativity$. However, even though there are quantitative differences between the original english text and its esperanto translation, the qualitative differences are very minutes, indicating in this case a translation relatively well respecting, along our analysis lines, the content of the author writing.
0802.4233
Adaptive Sum Power Iterative Waterfilling for MIMO Cognitive Radio Channels
cs.IT math.IT
In this paper, the sum capacity of the Gaussian Multiple Input Multiple Output (MIMO) Cognitive Radio Channel (MCC) is expressed as a convex problem with finite number of linear constraints, allowing for polynomial time interior point techniques to find the solution. In addition, a specialized class of sum power iterative waterfilling algorithms is determined that exploits the inherent structure of the sum capacity problem. These algorithms not only determine the maximizing sum capacity value, but also the transmit policies that achieve this optimum. The paper concludes by providing numerical results which demonstrate that the algorithm takes very few iterations to converge to the optimum.
0802.4270
Propagation Rules of Subsystem Codes
quant-ph cs.IT math.IT
We demonstrate propagation rules of subsystem code constructions by extending, shortening and combining given subsystem codes. Given an $[[n,k,r,d]]_q$ subsystem code, we drive new subsystem codes with parameters $[[n+1,k,r,\geq d]]_q$, $[[n-1,k+1,r,\geq d-1]]_q$, $[[n,k-1,r+1,d]]_q$. The interested readers shall consult our companion papers for upper and lower bounds on subsystem codes parameters, and introduction, trading dimensions, families, and references on subsystem codes [1][2][3] and references therein.
0802.4282
Distributed Opportunistic Scheduling For Ad-Hoc Communications Under Noisy Channel Estimation
cs.IT math.IT
Distributed opportunistic scheduling is studied for wireless ad-hoc networks, where many links contend for one channel using random access. In such networks, distributed opportunistic scheduling (DOS) involves a process of joint channel probing and distributed scheduling. It has been shown that under perfect channel estimation, the optimal DOS for maximizing the network throughput is a pure threshold policy. In this paper, this formalism is generalized to explore DOS under noisy channel estimation, where the transmission rate needs to be backed off from the estimated rate to reduce the outage. It is shown that the optimal scheduling policy remains to be threshold-based, and that the rate threshold turns out to be a function of the variance of the estimation error and be a functional of the backoff rate function. Since the optimal backoff rate is intractable, a suboptimal linear backoff scheme that backs off the estimated signal-to-noise ratio (SNR) and hence the rate is proposed. The corresponding optimal backoff ratio and rate threshold can be obtained via an iterative algorithm. Finally, simulation results are provided to illustrate the tradeoff caused by increasing training time to improve channel estimation at the cost of probing efficiency.
0802.4284
Distributed Opportunistic Scheduling for MIMO Ad-Hoc Networks
cs.IT math.IT
Distributed opportunistic scheduling (DOS) protocols are proposed for multiple-input multiple-output (MIMO) ad-hoc networks with contention-based medium access. The proposed scheduling protocols distinguish themselves from other existing works by their explicit design for system throughput improvement through exploiting spatial multiplexing and diversity in a {\em distributed} manner. As a result, multiple links can be scheduled to simultaneously transmit over the spatial channels formed by transmit/receiver antennas. Taking into account the tradeoff between feedback requirements and system throughput, we propose and compare protocols with different levels of feedback information. Furthermore, in contrast to the conventional random access protocols that ignore the physical channel conditions of contending links, the proposed protocols implement a pure threshold policy derived from optimal stopping theory, i.e. only links with threshold-exceeding channel conditions are allowed for data transmission. Simulation results confirm that the proposed protocols can achieve impressive throughput performance by exploiting spatial multiplexing and diversity.
0802.4291
Opportunistic Scheduling and Beamforming for MIMO-OFDMA Downlink Systems with Reduced Feedback
cs.IT math.IT
Opportunistic scheduling and beamforming schemes with reduced feedback are proposed for MIMO-OFDMA downlink systems. Unlike the conventional beamforming schemes in which beamforming is implemented solely by the base station (BS) in a per-subcarrier fashion, the proposed schemes take advantages of a novel channel decomposition technique to perform beamforming jointly by the BS and the mobile terminal (MT). The resulting beamforming schemes allow the BS to employ only {\em one} beamforming matrix (BFM) to form beams for {\em all} subcarriers while each MT completes the beamforming task for each subcarrier locally. Consequently, for a MIMO-OFDMA system with $Q$ subcarriers, the proposed opportunistic scheduling and beamforming schemes require only one BFM index and $Q$ supportable throughputs to be returned from each MT to the BS, in contrast to $Q$ BFM indices and $Q$ supportable throughputs required by the conventional schemes. The advantage of the proposed schemes becomes more evident when a further feedback reduction is achieved by grouping adjacent subcarriers into exclusive clusters and returning only cluster information from each MT. Theoretical analysis and computer simulation confirm the effectiveness of the proposed reduced-feedback schemes.
0802.4299
SINR Analysis of Opportunistic MIMO-SDMA Downlink Systems with Linear Combining
cs.IT math.IT
Opportunistic scheduling (OS) schemes have been proposed previously by the authors for multiuser MIMO-SDMA downlink systems with linear combining. In particular, it has been demonstrated that significant performance improvement can be achieved by incorporating low-complexity linear combining techniques into the design of OS schemes for MIMO-SDMA. However, this previous analysis was performed based on the effective signal-to-interference ratio (SIR), assuming an interference-limited scenario, which is typically a valid assumption in SDMA-based systems. It was shown that the limiting distribution of the effective SIR is of the Frechet type. Surprisingly, the corresponding scaling laws were found to follow $\epsilon\log K$ with $0<\epsilon<1$, rather than the conventional $\log\log K$ form. Inspired by this difference between the scaling law forms, in this paper a systematic approach is developed to derive asymptotic throughput and scaling laws based on signal-to-interference-noise ratio (SINR) by utilizing extreme value theory. The convergence of the limiting distribution of the effective SINR to the Gumbel type is established. The resulting scaling law is found to be governed by the conventional $\log\log K$ form. These novel results are validated by simulation results. The comparison of SIR and SINR-based analysis suggests that the SIR-based analysis is more computationally efficient for SDMA-based systems and it captures the asymptotic system performance with higher fidelity.
0802.4326
The Generation of Textual Entailment with NLML in an Intelligent Dialogue system for Language Learning CSIEC
cs.CL cs.AI cs.CY
This research report introduces the generation of textual entailment within the project CSIEC (Computer Simulation in Educational Communication), an interactive web-based human-computer dialogue system with natural language for English instruction. The generation of textual entailment (GTE) is critical to the further improvement of CSIEC project. Up to now we have found few literatures related with GTE. Simulating the process that a human being learns English as a foreign language we explore our naive approach to tackle the GTE problem and its algorithm within the framework of CSIEC, i.e. rule annotation in NLML, pattern recognition (matching), and entailment transformation. The time and space complexity of our algorithm is tested with some entailment examples. Further works include the rules annotation based on the English textbooks and a GUI interface for normal users to edit the entailment rules.
0802.4330
Eigenvalue Estimates and Mutual Information for the Linear Time-Varying Channel
cs.IT math.IT
We consider linear time-varying channels with additive white Gaussian noise. For a large class of such channels we derive rigorous estimates of the eigenvalues of the correlation matrix of the effective channel in terms of the sampled time-varying transfer function and, thus, provide a theoretical justification for a relationship that has been frequently observed in the literature. We then use this eigenvalue estimate to derive an estimate of the mutual information of the channel. Our approach is constructive and is based on a careful balance of the trade-off between approximate operator diagonalization, signal dimension loss, and accuracy of eigenvalue estimates.
0802.4344
An Improved Scheme for Initial Ranging in OFDMA-based Networks
cs.IT cs.OH math.IT
An efficient scheme for initial ranging has recently been proposed by X. Fu et al. in the context of orthogonal frequency-division multiple-access (OFDMA) networks based on the IEEE 802.16e-2005 standard. The proposed solution aims at estimating the power levels and timing offsets of the ranging subscriber stations (RSSs) without taking into account the effect of possible carrier frequency offsets (CFOs) between the received signals and the base station local reference. Motivated by the above problem, in the present work we design a novel ranging scheme for OFDMA in which the ranging signals are assumed to be misaligned both in time and frequency. Our goal is to estimate the timing errors and CFOs of each active RSS. Specifically, CFO estimation is accomplished by resorting to subspacebased methods while a least-squares approach is employed for timing recovery. Computer simulations are used to assess the effectiveness of the proposed solution and to make comparisons with existing alternatives.
0802.4363
Estimating the entropy of binary time series: Methodology, some theory and a simulation study
cs.IT math.IT math.ST stat.TH
Partly motivated by entropy-estimation problems in neuroscience, we present a detailed and extensive comparison between some of the most popular and effective entropy estimation methods used in practice: The plug-in method, four different estimators based on the Lempel-Ziv (LZ) family of data compression algorithms, an estimator based on the Context-Tree Weighting (CTW) method, and the renewal entropy estimator. **Methodology. Three new entropy estimators are introduced. For two of the four LZ-based estimators, a bootstrap procedure is described for evaluating their standard error, and a practical rule of thumb is heuristically derived for selecting the values of their parameters. ** Theory. We prove that, unlike their earlier versions, the two new LZ-based estimators are consistent for every finite-valued, stationary and ergodic process. An effective method is derived for the accurate approximation of the entropy rate of a finite-state HMM with known distribution. Heuristic calculations are presented and approximate formulas are derived for evaluating the bias and the standard error of each estimator. ** Simulation. All estimators are applied to a wide range of data generated by numerous different processes with varying degrees of dependence and memory. Some conclusions drawn from these experiments include: (i) For all estimators considered, the main source of error is the bias. (ii) The CTW method is repeatedly and consistently seen to provide the most accurate results. (iii) The performance of the LZ-based estimators is often comparable to that of the plug-in method. (iv) The main drawback of the plug-in method is its computational inefficiency.
0802.4390
Low Complexity Sphere Decoding for Spatial Multiplexing MIMO
cs.IT math.IT
In this paper we present a novel method for decoding multiple input - multiple output (MIMO) transmission, which combines sphere decoding (SD) and zero forcing (ZF) techniques to provide near optimal low complexity and high performance constant time modified sphere decoding algorithm. This algorithm was designed especially for large number of transmit antennas, and allows efficient implementation in hardware. We do this by limiting the number of overall SD iterations. Moreover, we make sure that matrices with high condition number are more likely to undergo SD.
0802.4450
A Study On Distributed Model Predictive Consensus
cs.MA
We investigate convergence properties of a proposed distributed model predictive control (DMPC) scheme, where agents negotiate to compute an optimal consensus point using an incremental subgradient method based on primal decomposition as described in Johansson et al. [2006, 2007]. The objective of the distributed control strategy is to agree upon and achieve an optimal common output value for a group of agents in the presence of constraints on the agent dynamics using local predictive controllers. Stability analysis using a receding horizon implementation of the distributed optimal consensus scheme is performed. Conditions are given under which convergence can be obtained even if the negotiations do not reach full consensus.
0803.0014
Automated Termination Proofs for Logic Programs by Term Rewriting
cs.LO cs.AI cs.PL
There are two kinds of approaches for termination analysis of logic programs: "transformational" and "direct" ones. Direct approaches prove termination directly on the basis of the logic program. Transformational approaches transform a logic program into a term rewrite system (TRS) and then analyze termination of the resulting TRS instead. Thus, transformational approaches make all methods previously developed for TRSs available for logic programs as well. However, the applicability of most existing transformations is quite restricted, as they can only be used for certain subclasses of logic programs. (Most of them are restricted to well-moded programs.) In this paper we improve these transformations such that they become applicable for any definite logic program. To simulate the behavior of logic programs by TRSs, we slightly modify the notion of rewriting by permitting infinite terms. We show that our transformation results in TRSs which are indeed suitable for automated termination analysis. In contrast to most other methods for termination of logic programs, our technique is also sound for logic programming without occur check, which is typically used in practice. We implemented our approach in the termination prover AProVE and successfully evaluated it on a large collection of examples.
0803.0032
Composition Attacks and Auxiliary Information in Data Privacy
cs.DB cs.CR
Privacy is an increasingly important aspect of data publishing. Reasoning about privacy, however, is fraught with pitfalls. One of the most significant is the auxiliary information (also called external knowledge, background knowledge, or side information) that an adversary gleans from other channels such as the web, public records, or domain knowledge. This paper explores how one can reason about privacy in the face of rich, realistic sources of auxiliary information. Specifically, we investigate the effectiveness of current anonymization schemes in preserving privacy when multiple organizations independently release anonymized data about overlapping populations. 1. We investigate composition attacks, in which an adversary uses independent anonymized releases to breach privacy. We explain why recently proposed models of limited auxiliary information fail to capture composition attacks. Our experiments demonstrate that even a simple instance of a composition attack can breach privacy in practice, for a large class of currently proposed techniques. The class includes k-anonymity and several recent variants. 2. On a more positive note, certain randomization-based notions of privacy (such as differential privacy) provably resist composition attacks and, in fact, the use of arbitrary side information. This resistance enables stand-alone design of anonymization schemes, without the need for explicitly keeping track of other releases. We provide a precise formulation of this property, and prove that an important class of relaxations of differential privacy also satisfy the property. This significantly enlarges the class of protocols known to enable modular design.
0803.0053
Mobile Agents for Content-Based WWW Distributed Image Retrieval
cs.DC cs.IR
At present, the de-facto standard for providing contents in the Internet is the World Wide Web. A technology, which is now emerging on the Web, is Content-Based Image Retrieval (CBIR). CBIR applies methods and algorithms from computer science to analyse and index images based on their visual content. Mobile agents push the flexibility of distributed systems to their limits since not only computations are dynamically distributed but also the code that performs them. The current commercial applet-based methodologies for accessing image database systems offer limited flexibility, scalability and robustness. In this paper the author proposes a new framework for content-based WWW distributed image retrieval based on Java-based mobile agents. The implementation of the framework shows that its performance is comparable to, and in some cases outperforms, the current approach.
0803.0146
Polynomial time algorithms for bi-criteria, multi-objective and ratio problems in clustering and imaging. Part I: Normalized cut and ratio regions
cs.CV cs.DM
Partitioning and grouping of similar objects plays a fundamental role in image segmentation and in clustering problems. In such problems a typical goal is to group together similar objects, or pixels in the case of image processing. At the same time another goal is to have each group distinctly dissimilar from the rest and possibly to have the group size fairly large. These goals are often combined as a ratio optimization problem. One example of such problem is the normalized cut problem, another is the ratio regions problem. We devise here the first polynomial time algorithms solving these problems optimally. The algorithms are efficient and combinatorial. This contrasts with the heuristic approaches used in the image segmentation literature that formulate those problems as nonlinear optimization problems, which are then relaxed and solved with spectral techniques in real numbers. These approaches not only fail to deliver an optimal solution, but they are also computationally expensive. The algorithms presented here use as a subroutine a minimum $s,t-cut procedure on a related graph which is of polynomial size. The output consists of the optimal solution to the respective ratio problem, as well as a sequence of nested solution with respect to any relative weighting of the objectives of the numerator and denominator. An extension of the results here to bi-criteria and multi-criteria objective functions is presented in part II.
0803.0189
Quiescence of Self-stabilizing Gossiping among Mobile Agents in Graphs
cs.DC cs.PF cs.RO
This paper considers gossiping among mobile agents in graphs: agents move on the graph and have to disseminate their initial information to every other agent. We focus on self-stabilizing solutions for the gossip problem, where agents may start from arbitrary locations in arbitrary states. Self-stabilization requires (some of the) participating agents to keep moving forever, hinting at maximizing the number of agents that could be allowed to stop moving eventually. This paper formalizes the self-stabilizing agent gossip problem, introduces the quiescence number (i.e., the maximum number of eventually stopping agents) of self-stabilizing solutions and investigates the quiescence number with respect to several assumptions related to agent anonymity, synchrony, link duplex capacity, and whiteboard capacity.
0803.0194
Acquisition Accuracy Evaluation in Visual Inspection Systems - a Practical Approach
cs.CV cs.MM
This paper draws a proposal of a set of parameters and methods for accuracy evaluation of visual inspection systems. The case of a monochrome board is treated, but practically all conclusions and methods may be extended for colour acquisition. Basically, the proposed parameters are grouped in five sets as follows:Internal noise;Video ADC cuantisation parameters;Analogue processing section parameters;Dominant frequencies;Synchronisation (lock-in) accuracy. On basis of this set of parameters was developed a software environment, in conjunction with a test signal generator that allows the "test" images. The paper also presents conclusions of evaluation for two types of video acquisition boards
0803.0265
Blind Fingerprinting
cs.IT math.IT
We study blind fingerprinting, where the host sequence into which fingerprints are embedded is partially or completely unknown to the decoder. This problem relates to a multiuser version of the Gel'fand-Pinsker problem. The number of colluders and the collusion channel are unknown, and the colluders and the fingerprint embedder are subject to distortion constraints. We propose a conditionally constant-composition random binning scheme and a universal decoding rule and derive the corresponding false-positive and false-negative error exponents. The encoder is a stacked binning scheme and makes use of an auxiliary random sequence. The decoder is a {\em maximum doubly-penalized mutual information decoder}, where the significance of each candidate coalition is assessed relative to a threshold that trades off false-positive and false-negative error exponents. The penalty is proportional to coalition size and is a function of the conditional type of host sequence. Positive exponents are obtained at all rates below a certain value, which is therefore a lower bound on public fingerprinting capacity. We conjecture that this value is the public fingerprinting capacity. A simpler threshold decoder is also given, which has similar universality properties but also lower achievable rates. An upper bound on public fingerprinting capacity is also derived.
0803.0398
In-depth analysis of the Naming Game dynamics: the homogeneous mixing case
physics.soc-ph cond-mat.stat-mech cs.GT cs.MA
Language emergence and evolution has recently gained growing attention through multi-agent models and mathematical frameworks to study their behavior. Here we investigate further the Naming Game, a model able to account for the emergence of a shared vocabulary of form-meaning associations through social/cultural learning. Due to the simplicity of both the structure of the agents and their interaction rules, the dynamics of this model can be analyzed in great detail using numerical simulations and analytical arguments. This paper first reviews some existing results and then presents a new overall understanding.
0803.0405
Multi-dimensional sparse time series: feature extraction
cs.MM cs.IR
We show an analysis of multi-dimensional time series via entropy and statistical linguistic techniques. We define three markers encoding the behavior of the series, after it has been translated into a multi-dimensional symbolic sequence. The leading component and the trend of the series with respect to a mobile window analysis result from the entropy analysis and label the dynamical evolution of the series. The diversification formalizes the differentiation in the use of recurrent patterns, from a Zipf law point of view. These markers are the starting point of further analysis such as classification or clustering of large database of multi-dimensional time series, prediction of future behavior and attribution of new data. We also present an application to economic data. We deal with measurements of money investments of some business companies in advertising market for different media sources.
0803.0428
Zero-Forcing Precoding for Frequency Selective MIMO Channels with $H^\infty$ Criterion and Causality Constraint
cs.IT math.IT
We consider zero-forcing equalization of frequency selective MIMO channels by causal and linear time-invariant precoders in the presence of intersymbol interference. Our motivation is twofold. First, we are concerned with the optimal performance of causal precoders from a worst case point of view. Therefore we construct an optimal causal precoder, whereas contrary to other works our construction is not limited to finite or rational impulse responses. Moreover we derive a novel numerical approach to computation of the optimal perfomance index achievable by causal precoders for given channels. This quantity is important in the numerical determination of optimal precoders.
0803.0450
Inferring Neuronal Network Connectivity from Spike Data: A Temporal Datamining Approach
cs.DB q-bio.NC
Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent developments in electrophysiology and imaging allow one to simultaneously record activities of hundreds of neurons. Inferring the underlying neuronal connectivity patterns from such multi-neuronal spike train data streams is a challenging statistical and computational problem. This task involves finding significant temporal patterns from vast amounts of symbolic time series data. In this paper we show that the frequent episode mining methods from the field of temporal data mining can be very useful in this context. In the frequent episode discovery framework, the data is viewed as a sequence of events, each of which is characterized by an event type and its time of occurrence and episodes are certain types of temporal patterns in such data. Here we show that, using the set of discovered frequent episodes from multi-neuronal data, one can infer different types of connectivity patterns in the neural system that generated it. For this purpose, we introduce the notion of mining for frequent episodes under certain temporal constraints; the structure of these temporal constraints is motivated by the application. We present algorithms for discovering serial and parallel episodes under these temporal constraints. Through extensive simulation studies we demonstrate that these methods are useful for unearthing patterns of neuronal network connectivity.
0803.0597
Cooperative Spectrum Sensing Using Random Matrix Theory
cs.IT math.IT
In this paper, using tools from asymptotic random matrix theory, a new cooperative scheme for frequency band sensing is introduced for both AWGN and fading channels. Unlike previous works in the field, the new scheme does not require the knowledge of the noise statistics or its variance and is related to the behavior of the largest and smallest eigenvalue of random matrices. Remarkably, simulations show that the asymptotic claims hold even for a small number of observations (which makes it convenient for time-varying topologies), outperforming classical energy detection techniques.
0803.0610
On the Approximate Eigenstructure of Time-Varying Channels
cs.IT math.IT
In this article we consider the approximate description of doubly--dispersive channels by its symbol. We focus on channel operators with compactly supported spreading, which are widely used to represent fast fading multipath communication channels. The concept of approximate eigenstructure is introduced, which measures the accuracy E_p of the approximation of the channel operation as a pure multiplication in a given L_p-norm. Two variants of such an approximate Weyl symbol calculus are studied, which have important applications in several models for time--varying mobile channels. Typically, such channels have random spreading functions (inverse Weyl transform) defined on a common support U of finite non--zero size such that approximate eigenstructure has to be measured with respect to certain norms of the spreading process. We derive several explicit relations to the size |U| of the support. We show that the characterization of the ratio of E_p to some L_q-norm of the spreading function is related to weighted norms of ambiguity and Wigner functions. We present the connection to localization operators and give new bounds on the ability of localization of ambiguity functions and Wigner functions in U. Our analysis generalizes and improves recent results for the case p=2 and q=1.
0803.0632
Network Coding for Distributed Storage Systems
cs.NI cs.IT math.IT
Distributed storage systems provide reliable access to data through redundancy spread over individually unreliable nodes. Application scenarios include data centers, peer-to-peer storage systems, and storage in wireless networks. Storing data using an erasure code, in fragments spread across nodes, requires less redundancy than simple replication for the same level of reliability. However, since fragments must be periodically replaced as nodes fail, a key question is how to generate encoded fragments in a distributed way while transferring as little data as possible across the network. For an erasure coded system, a common practice to repair from a node failure is for a new node to download subsets of data stored at a number of surviving nodes, reconstruct a lost coded block using the downloaded data, and store it at the new node. We show that this procedure is sub-optimal. We introduce the notion of regenerating codes, which allow a new node to download \emph{functions} of the stored data from the surviving nodes. We show that regenerating codes can significantly reduce the repair bandwidth. Further, we show that there is a fundamental tradeoff between storage and repair bandwidth which we theoretically characterize using flow arguments on an appropriately constructed graph. By invoking constructive results in network coding, we introduce regenerating codes that can achieve any point in this optimal tradeoff.
0803.0731
Complexity Analysis of Reed-Solomon Decoding over GF(2^m) Without Using Syndromes
cs.IT cs.CC cs.DS math.IT
For the majority of the applications of Reed-Solomon (RS) codes, hard decision decoding is based on syndromes. Recently, there has been renewed interest in decoding RS codes without using syndromes. In this paper, we investigate the complexity of syndromeless decoding for RS codes, and compare it to that of syndrome-based decoding. Aiming to provide guidelines to practical applications, our complexity analysis differs in several aspects from existing asymptotic complexity analysis, which is typically based on multiplicative fast Fourier transform (FFT) techniques and is usually in big O notation. First, we focus on RS codes over characteristic-2 fields, over which some multiplicative FFT techniques are not applicable. Secondly, due to moderate block lengths of RS codes in practice, our analysis is complete since all terms in the complexities are accounted for. Finally, in addition to fast implementation using additive FFT techniques, we also consider direct implementation, which is still relevant for RS codes with moderate lengths. Comparing the complexities of both syndromeless and syndrome-based decoding algorithms based on direct and fast implementations, we show that syndromeless decoding algorithms have higher complexities than syndrome-based ones for high rate RS codes regardless of the implementation. Both errors-only and errors-and-erasures decoding are considered in this paper. We also derive tighter bounds on the complexities of fast polynomial multiplications based on Cantor's approach and the fast extended Euclidean algorithm.
0803.0755
Toeplitz Block Matrices in Compressed Sensing
cs.IT math.IT math.PR
Recent work in compressed sensing theory shows that $n\times N$ independent and identically distributed (IID) sensing matrices whose entries are drawn independently from certain probability distributions guarantee exact recovery of a sparse signal with high probability even if $n\ll N$. Motivated by signal processing applications, random filtering with Toeplitz sensing matrices whose elements are drawn from the same distributions were considered and shown to also be sufficient to recover a sparse signal from reduced samples exactly with high probability. This paper considers Toeplitz block matrices as sensing matrices. They naturally arise in multichannel and multidimensional filtering applications and include Toeplitz matrices as special cases. It is shown that the probability of exact reconstruction is also high. Their performance is validated using simulations.
0803.0764
Asymmetric and Symmetric Subsystem BCH Codes and Beyond
quant-ph cs.IT math.IT
Recently, the theory of quantum error control codes has been extended to subsystem codes over symmetric and asymmetric quantum channels -- qubit-flip and phase-shift errors may have equal or different probabilities. Previous work in constructing quantum error control codes has focused on code constructions for symmetric quantum channels. In this paper, we develop a theory and establish the connection between asymmetric quantum codes and subsystem codes. We present families of subsystem and asymmetric quantum codes derived, once again, from classical BCH and RS codes over finite fields. Particularly, we derive an interesting asymmetric and symmetric subsystem codes based on classical BCH codes with parameters $[[n,k,r,d]]_q$, $[[n,k,r,d_z/d_x]]_q$ and $[[n,k',0,d_z/d_x]]_q$ for arbitrary values of code lengths and dimensions. We establish asymmetric Singleton and Hamming bounds on asymmetric quantum and subsystem code parameters; and derive optimal asymmetric MDS subsystem codes. Finally, our constructions are well explained by an illustrative example. This paper is written on the occasion of the 50th anniversary of the discovery of classical BCH codes and their quantum counterparts were derived nearly 10 years ago.
0803.0778
Constant-Rank Codes
cs.IT math.IT
Constant-dimension codes have recently received attention due to their significance to error control in noncoherent random network coding. In this paper, we show that constant-rank codes are closely related to constant-dimension codes and we study the properties of constant-rank codes. We first introduce a relation between vectors in $\mathrm{GF}(q^m)^n$ and subspaces of $\mathrm{GF}(q)^m$ or $\mathrm{GF}(q)^n$, and use it to establish a relation between constant-rank codes and constant-dimension codes. We then derive bounds on the maximum cardinality of constant-rank codes with given rank weight and minimum rank distance. Finally, we investigate the asymptotic behavior of the maximal cardinality of constant-rank codes with given rank weight and minimum rank distance.
0803.0811
Subspace Pursuit for Compressive Sensing Signal Reconstruction
cs.NA cs.IT math.IT
We propose a new method for reconstruction of sparse signals with and without noisy perturbations, termed the subspace pursuit algorithm. The algorithm has two important characteristics: low computational complexity, comparable to that of orthogonal matching pursuit techniques when applied to very sparse signals, and reconstruction accuracy of the same order as that of LP optimization methods. The presented analysis shows that in the noiseless setting, the proposed algorithm can exactly reconstruct arbitrary sparse signals provided that the sensing matrix satisfies the restricted isometry property with a constant parameter. In the noisy setting and in the case that the signal is not exactly sparse, it can be shown that the mean squared error of the reconstruction is upper bounded by constant multiples of the measurement and signal perturbation energies.
0803.0822
Website Optimization through Mining User Navigational Pattern
cs.IR
With the World Wide Web's ubiquity increase and the rapid development of various online businesses, the complexity of web sites grow. The analysis of web user's navigational pattern within a web site can provide useful information for server performance enhancements, restructuring a website and direct marketing in e-commerce etc. In this paper, an algorithm is proposed for mining such navigation patterns. The key insight is that users access information of interest and follow a certain path while navigating a web site. If they don't find it, they would backtrack and choose among the alternate paths till they reach the destination. The point they backtrack is the Intermediate Reference Location. Identifying such Intermediate locations and destinations out of the pattern will be the main endeavor in the rest of this report.
0803.0875
Vandermonde Frequency Division Multiplexing for Cognitive Radio
cs.IT math.IT
We consider a cognitive radio scenario where a primary and a secondary user wish to communicate with their corresponding receivers simultaneously over frequency selective channels. Under realistic assumptions that the secondary transmitter has no side information about the primary's message and each transmitter knows only its local channels, we propose a Vandermonde precoder that cancels the interference from the secondary user by exploiting the redundancy of a cyclic prefix. Our numerical examples show that VFDM, with an appropriate design of the input covariance, enables the secondary user to achieve a considerable rate while generating zero interference to the primary user.
0803.0924
What Can We Learn Privately?
cs.LG cs.CC cs.CR cs.DB
Learning problems form an important category of computational tasks that generalizes many of the computations researchers apply to large real-life data sets. We ask: what concept classes can be learned privately, namely, by an algorithm whose output does not depend too heavily on any one input or specific training example? More precisely, we investigate learning algorithms that satisfy differential privacy, a notion that provides strong confidentiality guarantees in contexts where aggregate information is released about a database containing sensitive information about individuals. We demonstrate that, ignoring computational constraints, it is possible to privately agnostically learn any concept class using a sample size approximately logarithmic in the cardinality of the concept class. Therefore, almost anything learnable is learnable privately: specifically, if a concept class is learnable by a (non-private) algorithm with polynomial sample complexity and output size, then it can be learned privately using a polynomial number of samples. We also present a computationally efficient private PAC learner for the class of parity functions. Local (or randomized response) algorithms are a practical class of private algorithms that have received extensive investigation. We provide a precise characterization of local private learning algorithms. We show that a concept class is learnable by a local algorithm if and only if it is learnable in the statistical query (SQ) model. Finally, we present a separation between the power of interactive and noninteractive local learning algorithms.
0803.0954
Selective association rule generation
cs.DB cs.DS
Mining association rules is a popular and well researched method for discovering interesting relations between variables in large databases. A practical problem is that at medium to low support values often a large number of frequent itemsets and an even larger number of association rules are found in a database. A widely used approach is to gradually increase minimum support and minimum confidence or to filter the found rules using increasingly strict constraints on additional measures of interestingness until the set of rules found is reduced to a manageable size. In this paper we describe a different approach which is based on the idea to first define a set of ``interesting'' itemsets (e.g., by a mixture of mining and expert knowledge) and then, in a second step to selectively generate rules for only these itemsets. The main advantage of this approach over increasing thresholds or filtering rules is that the number of rules found is significantly reduced while at the same time it is not necessary to increase the support and confidence thresholds which might lead to missing important information in the database.
0803.0966
New probabilistic interest measures for association rules
cs.DB stat.ML
Mining association rules is an important technique for discovering meaningful patterns in transaction databases. Many different measures of interestingness have been proposed for association rules. However, these measures fail to take the probabilistic properties of the mined data into account. In this paper, we start with presenting a simple probabilistic framework for transaction data which can be used to simulate transaction data when no associations are present. We use such data and a real-world database from a grocery outlet to explore the behavior of confidence and lift, two popular interest measures used for rule mining. The results show that confidence is systematically influenced by the frequency of the items in the left hand side of rules and that lift performs poorly to filter random noise in transaction data. Based on the probabilistic framework we develop two new interest measures, hyper-lift and hyper-confidence, which can be used to filter or order mined association rules. The new measures show significantly better performance than lift for applications where spurious rules are problematic.