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0811.4200
Two Models for Noisy Feedback in MIMO Channels
cs.IT math.IT
Two distinct models of feedback, suited for FDD (Frequency Division Duplex) and TDD (Frequency Division Duplex) systems respectively, have been widely studied in the literature. In this paper, we compare these two models of feedback in terms of the diversity multiplexing tradeoff for varying amount of channel state information at the terminals. We find that, when all imperfections are accounted for, the maximum achievable diversity order in FDD systems matches the diversity order in TDD systems. TDD systems achieve better diversity order at higher multiplexing gains. In FDD systems, the maximum diversity order can be achieved with just a single bit of feedback. Additional bits of feedback (perfect or imperfect) do not affect the diversity order if the receiver does not know the channel state information.
0811.4227
Entanglement-assisted communication of classical and quantum information
quant-ph cs.IT math.IT
We consider the problem of transmitting classical and quantum information reliably over an entanglement-assisted quantum channel. Our main result is a capacity theorem that gives a three-dimensional achievable rate region. Points in the region are rate triples, consisting of the classical communication rate, the quantum communication rate, and the entanglement consumption rate of a particular coding scheme. The crucial protocol in achieving the boundary points of the capacity region is a protocol that we name the classically-enhanced father protocol. The classically-enhanced father protocol is more general than other protocols in the family tree of quantum Shannon theoretic protocols, in the sense that several previously known quantum protocols are now child protocols of it. The classically-enhanced father protocol also shows an improvement over a time-sharing strategy for the case of a qubit dephasing channel--this result justifies the need for simultaneous coding of classical and quantum information over an entanglement-assisted quantum channel. Our capacity theorem is of a multi-letter nature (requiring a limit over many uses of the channel), but it reduces to a single-letter characterization for at least three channels: the completely depolarizing channel, the quantum erasure channel, and the qubit dephasing channel.
0811.4339
Finite Lattice-Size Effects in MIMO Detection
cs.IT math.IT
Many powerful data detection algorithms employed in multiple-input multiple-output (MIMO) communication systems, such as sphere decoding (SD) and lattice-reduction (LR)-aided detection, were initially designed for infinite lattices. Detection in MIMO systems is, however, based on finite lattices. In this paper, we systematically study the consequences of finite lattice-size for the performance and complexity of MIMO detection algorithms formulated for infinite lattices. Specifically, we find, considering performance and complexity, that LR does not seem to offer advantages when used in conjunction with SD.
0811.4346
Dynamic Indexability: The Query-Update Tradeoff for One-Dimensional Range Queries
cs.DS cs.DB
The B-tree is a fundamental secondary index structure that is widely used for answering one-dimensional range reporting queries. Given a set of $N$ keys, a range query can be answered in $O(\log_B \nm + \frac{K}{B})$ I/Os, where $B$ is the disk block size, $K$ the output size, and $M$ the size of the main memory buffer. When keys are inserted or deleted, the B-tree is updated in $O(\log_B N)$ I/Os, if we require the resulting changes to be committed to disk right away. Otherwise, the memory buffer can be used to buffer the recent updates, and changes can be written to disk in batches, which significantly lowers the amortized update cost. A systematic way of batching up updates is to use the logarithmic method, combined with fractional cascading, resulting in a dynamic B-tree that supports insertions in $O(\frac{1}{B}\log\nm)$ I/Os and queries in $O(\log\nm + \frac{K}{B})$ I/Os. Such bounds have also been matched by several known dynamic B-tree variants in the database literature. In this paper, we prove that for any dynamic one-dimensional range query index structure with query cost $O(q+\frac{K}{B})$ and amortized insertion cost $O(u/B)$, the tradeoff $q\cdot \log(u/q) = \Omega(\log B)$ must hold if $q=O(\log B)$. For most reasonable values of the parameters, we have $\nm = B^{O(1)}$, in which case our query-insertion tradeoff implies that the bounds mentioned above are already optimal. Our lower bounds hold in a dynamic version of the {\em indexability model}, which is of independent interests.
0811.4349
Anti Plagiarism Application with Algorithm Karp-Rabin at Thesis in Gunadarma University
cs.IT cs.DL math.IT
Plagiarism that is plagiarizing or composition retrieval, opinion, etcetera from other people and makes it is likely composition and opinion him-self. Plagiarism can be considered to be crime because stealing others copyrights. Like action a student copying some part of writings without valid permission from the original writer. In education world, plagiarism perpetrator can get the devil to pay from school/university. Plagiarism perpetrator conceived of plagiator. This thing is possible unable to be paid attention by the side of campus because of limitation from some interconnected factors for example student amounts Gunadarma University reaching thousands and incommensurate to tester amounts or lecturer the side of campus in charge directs problem thesis. In this paper, an application have been developed in order to check and look for 5 type percentage similarity from a thesis with other one at certain part or chapters. Percentage got that is 0%, under 15%, between 15-50%, up to 50% and 100%. So it should be expected that the results could be used by thesis advisor and also thesis examiner from the Student at Gunadarma University.
0811.4354
Soft-Input Soft-Output Sphere Decoding
cs.IT math.IT
Soft-input soft-output (SISO) detection algorithms form the basis for iterative decoding. The associated computational complexity often poses significant challenges for practical receiver implementations, in particular in the context of multiple-input multiple-output wireless systems. In this paper, we present a low-complexity SISO sphere decoder which is based on the single tree search paradigm, proposed originally for soft-output detection in Studer et al., IEEE J-SAC, 2008. The algorithm incorporates clipping of the extrinsic log-likelihood ratios in the tree search, which not only results in significant complexity savings, but also allows to cover a large performance/complexity trade-off region by adjusting a single parameter.
0811.4391
Cross-Layer Link Adaptation Design for Relay Channels with Cooperative ARQ Protocol
cs.IT math.IT
The cooperative automatic repeat request (C-ARQ) is a link layer relaying protocol which exploits the spatial diversity and allows the relay node to retransmit the source data packet to the destination, when the latter is unable to decode the source data correctly. This paper presents a cross-layer link adaptation design for C-ARQ based relay channels in which both source and relay nodes employ adaptive modulation coding and power adaptation at the physical layer. For this scenario, we first derive closed-form expressions for the system spectral efficiency and average power consumption. We then present a low complexity iterative algorithm to find the optimized adaptation solution by maximizing the spectral efficiency subject to a packet loss rate (PLR) and an average power consumption constraint. The results indicate that the proposed adaptation scheme enhances the spectral efficiency noticeably when compared to other adaptive schemes, while guaranteeing the required PLR performance.
0811.4395
List Decoding Tensor Products and Interleaved Codes
cs.IT math.IT
We design the first efficient algorithms and prove new combinatorial bounds for list decoding tensor products of codes and interleaved codes. We show that for {\em every} code, the ratio of its list decoding radius to its minimum distance stays unchanged under the tensor product operation (rather than squaring, as one might expect). This gives the first efficient list decoders and new combinatorial bounds for some natural codes including multivariate polynomials where the degree in each variable is bounded. We show that for {\em every} code, its list decoding radius remains unchanged under $m$-wise interleaving for an integer $m$. This generalizes a recent result of Dinur et al \cite{DGKS}, who proved such a result for interleaved Hadamard codes (equivalently, linear transformations). Using the notion of generalized Hamming weights, we give better list size bounds for {\em both} tensoring and interleaving of binary linear codes. By analyzing the weight distribution of these codes, we reduce the task of bounding the list size to bounding the number of close-by low-rank codewords. For decoding linear transformations, using rank-reduction together with other ideas, we obtain list size bounds that are tight over small fields.
0811.4397
Joint Adaptive Modulation-Coding and Cooperative ARQ for Wireless Relay Networks
cs.IT math.IT
This paper presents a cross-layer approach to jointly design adaptive modulation and coding (AMC) at the physical layer and cooperative truncated automatic repeat request (ARQ) protocol at the data link layer. We first derive an exact closed form expression for the spectral efficiency of the proposed joint AMC-cooperative ARQ scheme. Aiming at maximizing this system performance measure, we then optimize an AMC scheme which directly satisfies a prescribed packet loss rate constraint at the data-link layer. The results indicate that utilizing cooperative ARQ as a retransmission strategy, noticeably enhances the spectral efficiency compared with the system that employs AMC alone at the physical layer. Moreover, the proposed adaptive rate cooperative ARQ scheme outperforms the fixed rate counterpart when the transmission modes at the source and relay are chosen based on the channel statistics. This in turn quantifies the possible gain achieved by joint design of AMC and ARQ in wireless relay networks.
0811.4403
Joint Adaptive Modulation Coding and Cooperative ARQ over Relay Channels-Applications to Land Mobile Satellite Communications
cs.IT math.IT
In a cooperative relay network, a relay node (R) facilitates data transmission to the destination node (D), when the latter is unable to decode the source node (S) data correctly. This paper considers such a system model and presents a cross-layer approach to jointly design adaptive modulation and coding (AMC) at the physical layer and cooperative truncated automatic repeat request (ARQ) protocol at the data link layer. We first derive a closed form expression for the spectral efficiency of the joint cooperative ARQ-AMC scheme. Aiming at maximizing this performance measure, we then optimize two AMC schemes for S-D and R-D links, which directly satisfy a prescribed packet loss rate constraint. As an interesting application, we also consider the problem of joint link adaptation and blockage mitigation in land mobile satellite communications (LMSC). We also present a new relay-assisted transmission protocol for LMSC, which delivers the source data to the destination via the relaying link, when the S-D channel is in outage. Numerical results indicate that the proposed schemes noticeably enhances the spectral efficiency compared to a system, which uses a conventional ARQ-AMC scheme at the S-D link, or a system which employs an optimized fixed rate cooperative-ARQ protocol.
0811.4413
A Spectral Algorithm for Learning Hidden Markov Models
cs.LG cs.AI
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computationally hard (under cryptographic assumptions), and practitioners typically resort to search heuristics which suffer from the usual local optima issues. We prove that under a natural separation condition (bounds on the smallest singular value of the HMM parameters), there is an efficient and provably correct algorithm for learning HMMs. The sample complexity of the algorithm does not explicitly depend on the number of distinct (discrete) observations---it implicitly depends on this quantity through spectral properties of the underlying HMM. This makes the algorithm particularly applicable to settings with a large number of observations, such as those in natural language processing where the space of observation is sometimes the words in a language. The algorithm is also simple, employing only a singular value decomposition and matrix multiplications.
0811.4458
Learning Class-Level Bayes Nets for Relational Data
cs.LG cs.AI
Many databases store data in relational format, with different types of entities and information about links between the entities. The field of statistical-relational learning (SRL) has developed a number of new statistical models for such data. In this paper we focus on learning class-level or first-order dependencies, which model the general database statistics over attributes of linked objects and links (e.g., the percentage of A grades given in computer science classes). Class-level statistical relationships are important in themselves, and they support applications like policy making, strategic planning, and query optimization. Most current SRL methods find class-level dependencies, but their main task is to support instance-level predictions about the attributes or links of specific entities. We focus only on class-level prediction, and describe algorithms for learning class-level models that are orders of magnitude faster for this task. Our algorithms learn Bayes nets with relational structure, leveraging the efficiency of single-table nonrelational Bayes net learners. An evaluation of our methods on three data sets shows that they are computationally feasible for realistic table sizes, and that the learned structures represent the statistical information in the databases well. After learning compiles the database statistics into a Bayes net, querying these statistics via Bayes net inference is faster than with SQL queries, and does not depend on the size of the database.
0811.4483
Wide spread spectrum watermarking with side information and interference cancellation
cs.MM cs.IT math.IT
Nowadays, a popular method used for additive watermarking is wide spread spectrum. It consists in adding a spread signal into the host document. This signal is obtained by the sum of a set of carrier vectors, which are modulated by the bits to be embedded. To extract these embedded bits, weighted correlations between the watermarked document and the carriers are computed. Unfortunately, even without any attack, the obtained set of bits can be corrupted due to the interference with the host signal (host interference) and also due to the interference with the others carriers (inter-symbols interference (ISI) due to the non-orthogonality of the carriers). Some recent watermarking algorithms deal with host interference using side informed methods, but inter-symbols interference problem is still open. In this paper, we deal with interference cancellation methods, and we propose to consider ISI as side information and to integrate it into the host signal. This leads to a great improvement of extraction performance in term of signal-to-noise ratio and/or watermark robustness.
0811.4489
Automatic Generation of the Axial Lines of Urban Environments to Capture What We Perceive
cs.CG cs.CV
Based on the concepts of isovists and medial axes, we developed a set of algorithms that can automatically generate axial lines for representing individual linearly stretched parts of open space of an urban environment. Open space is the space between buildings, where people can freely move around. The generation of the axial lines has been a key aspect of space syntax research, conventionally relying on hand-drawn axial lines of an urban environment, often called axial map, for urban morphological analysis. Although various attempts have been made towards an automatic solution, few of them can produce the axial map that consists of the least number of longest visibility lines, and none of them really works for different urban environments. Our algorithms provide a better solution than existing ones. Throughout this paper, we have also argued and demonstrated that the axial lines constitute a true skeleton, superior to medial axes, in capturing what we perceive about the urban environment. Keywords: Visibility, space syntax, topological analysis, medial axes, axial lines, isovists
0811.4565
Ergodic Capacity Analysis of Amplify-and-Forward MIMO Dual-Hop Systems
cs.IT math.IT
This paper presents an analytical characterization of the ergodic capacity of amplify-and-forward (AF) MIMO dual-hop relay channels, assuming that the channel state information is available at the destination terminal only. In contrast to prior results, our expressions apply for arbitrary numbers of antennas and arbitrary relay configurations. We derive an expression for the exact ergodic capacity, simplified closed-form expressions for the high SNR regime, and tight closed-form upper and lower bounds. These results are made possible to employing recent tools from finite-dimensional random matrix theory to derive new closed-form expressions for various statistical properties of the equivalent AF MIMO dual-hop relay channel, such as the distribution of an unordered eigenvalue and certain random determinant properties. Based on the analytical capacity expressions, we investigate the impact of the system and channel characteristics, such as the antenna configuration and the relay power gain. We also demonstrate a number of interesting relationships between the dual-hop AF MIMO relay channel and conventional point-to-point MIMO channels in various asymptotic regimes.
0811.4603
Frozen Footprints
cs.DL cs.IR
Bibliometrics has the ambitious goal of measuring science. To this end, it exploits the way science is disseminated trough scientific publications and the resulting citation network of scientific papers. We survey the main historical contributions to the field, the most interesting bibliometric indicators, and the most popular bibliometric data sources. Moreover, we discuss distributions commonly used to model bibliometric phenomena and give an overview of methods to build bibliometric maps of science.
0811.4630
Channel State Prediction, Feedback and Scheduling for a Multiuser MIMO-OFDM Downlink
cs.IT math.IT
We consider the downlink of a MIMO-OFDM wireless systems where the base-station (BS) has M antennas and serves K single-antenna user terminals (UT) with K larger than or equal to M. Users estimate their channel vectors from common downlink pilot symbols and feed back a prediction, which is used by the BS to compute the linear beamforming matrix for the next time slot and to select the users to be served according to the proportional fair scheduling (PFS) algorithm. We consider a realistic physical channel model used as a benchmark in standardization and some alternatives for the channel estimation and prediction scheme. We show that a parametric method based on ESPRIT is able to accurately predict the channel even for relatively high user mobility. However, there exists a class of channels characterized by large Doppler spread (high mobility) and clustered angular spread for which prediction is intrinsically difficult and all considered methods fail. We propose a modified PFS that take into account the "predictability" state of the UTs, and significantly outperform the classical PFS in the presence of prediction errors. The main conclusion of this work is that multiuser MIMO downlink yields very good performance even in the presence of high mobility users, provided that the nonpredictable users are handled appropriately
0811.4697
Informed stego-systems in active warden context: statistical undetectability and capacity
cs.IT cs.MM math.IT
Several authors have studied stego-systems based on Costa scheme, but just a few ones gave both theoretical and experimental justifications of these schemes performance in an active warden context. We provide in this paper a steganographic and comparative study of three informed stego-systems in active warden context: scalar Costa scheme, trellis-coded quantization and spread transform scalar Costa scheme. By leading on analytical formulations and on experimental evaluations, we show the advantages and limits of each scheme in term of statistical undetectability and capacity in the case of active warden. Such as the undetectability is given by the distance between the stego-signal and the cover distance. It is measured by the Kullback-Leibler distance.
0811.4699
Mapping Images with the Coherence Length Diagrams
cs.CV
Statistical pattern recognition methods based on the Coherence Length Diagram (CLD) have been proposed for medical image analyses, such as quantitative characterisation of human skin textures, and for polarized light microscopy of liquid crystal textures. Further investigations are made on image maps originated from such diagram and some examples related to irregularity of microstructures are shown.
0811.4700
Trellis-coded quantization for public-key steganography
cs.MM cs.IT math.IT
This paper deals with public-key steganography in the presence of a passive warden. The aim is to hide secret messages within cover-documents without making the warden suspicious, and without any preliminar secret key sharing. Whereas a practical attempt has been already done to provide a solution to this problem, it suffers of poor flexibility (since embedding and decoding steps highly depend on cover-signals statistics) and of little capacity compared to recent data hiding techniques. Using the same framework, this paper explores the use of trellis-coded quantization techniques (TCQ and turbo TCQ) to design a more efficient public-key scheme. Experiments on audio signals show great improvements considering Cachin's security criterion.
0811.4702
Information-theoretic resolution of perceptual WSS watermarking of non i.i.d. Gaussian signals
cs.IT cs.MM math.IT
The theoretical foundations of data hiding have been revealed by formulating the problem as message communication over a noisy channel. We revisit the problem in light of a more general characterization of the watermark channel and of weighted distortion measures. Considering spread spectrum based information hiding, we release the usual assumption of an i.i.d. cover signal. The game-theoretic resolution of the problem reveals a generalized characterization of optimum attacks. The paper then derives closed-form expressions for the different parameters exhibiting a practical embedding and extraction technique.
0811.4706
Comparing Measures of Sparsity
cs.IT math.IT
Sparsity of representations of signals has been shown to be a key concept of fundamental importance in fields such as blind source separation, compression, sampling and signal analysis. The aim of this paper is to compare several commonlyused sparsity measures based on intuitive attributes. Intuitively, a sparse representation is one in which a small number of coefficients contain a large proportion of the energy. In this paper six properties are discussed: (Robin Hood, Scaling, Rising Tide, Cloning, Bill Gates and Babies), each of which a sparsity measure should have. The main contributions of this paper are the proofs and the associated summary table which classify commonly-used sparsity measures based on whether or not they satisfy these six propositions and the corresponding proofs. Only one of these measures satisfies all six: The Gini Index. measures based on whether or not they satisfy these six propositions and the corresponding proofs. Only one of these measures satisfies all six: The Gini Index.
0811.4717
Prospective Study for Semantic Inter-Media Fusion in Content-Based Medical Image Retrieval
cs.IR cs.CL
One important challenge in modern Content-Based Medical Image Retrieval (CBMIR) approaches is represented by the semantic gap, related to the complexity of the medical knowledge. Among the methods that are able to close this gap in CBMIR, the use of medical thesauri/ontologies has interesting perspectives due to the possibility of accessing on-line updated relevant webservices and to extract real-time medical semantic structured information. The CBMIR approach proposed in this paper uses the Unified Medical Language System's (UMLS) Metathesaurus to perform a semantic indexing and fusion of medical media. This fusion operates before the query processing (retrieval) and works at an UMLS-compliant conceptual indexing level. Our purpose is to study various techniques related to semantic data alignment, preprocessing, fusion, clustering and retrieval, by evaluating the various techniques and highlighting future research directions. The alignment and the preprocessing are based on partial text/image retrieval feedback and on the data structure. We analyze various probabilistic, fuzzy and evidence-based approaches for the fusion process and different similarity functions for the retrieval process. All the proposed methods are evaluated on the Cross Language Evaluation Forum's (CLEF) medical image retrieval benchmark, by focusing also on a more homogeneous component medical image database: the Pathology Education Instructional Resource (PEIR).
0811.4718
On the Fourier Spectra of the Infinite Families of Quadratic APN Functions
cs.IT cs.CR cs.DM math.IT
It is well known that a quadratic function defined on a finite field of odd degree is almost bent (AB) if and only if it is almost perfect nonlinear (APN). For the even degree case there is no apparent relationship between the values in the Fourier spectrum of a function and the APN property. In this article we compute the Fourier spectrum of the new quadranomial family of APN functions. With this result, all known infinite families of APN functions now have their Fourier spectra and hence their nonlinearities computed.
0811.4733
Kinematic Analysis of a Serial - Parallel Machine Tool: the VERNE machine
cs.RO
The paper derives the inverse and the forward kinematic equations of a serial - parallel 5-axis machine tool: the VERNE machine. This machine is composed of a three-degree-of-freedom (DOF) parallel module and a two-DOF serial tilting table. The parallel module consists of a moving platform that is connected to a fixed base by three non-identical legs. These legs are connected in a way that the combined effects of the three legs lead to an over-constrained mechanism with complex motion. This motion is defined as a simultaneous combination of rotation and translation. In this paper we propose symbolical methods that able to calculate all kinematic solutions and identify the acceptable one by adding analytical constraint on the disposition of legs of the parallel module.
0811.4773
Two-way source coding with a helper
cs.IT math.IT
Consider the two-way rate-distortion problem in which a helper sends a common limited-rate message to both users based on side information at its disposal. We characterize the region of achievable rates and distortions where a Markov form (Helper)-(User 1)-(User 2) holds. The main insight of the result is that in order to achieve the optimal rate, the helper may use a binning scheme, as in Wyner-Ziv, where the side information at the decoder is the "further" user, namely, User 2. We derive these regions explicitly for the Gaussian sources with square error distortion, analyze a trade-off between the rate from the helper and the rate from the source, and examine a special case where the helper has the freedom to send different messages, at different rates, to the encoder and the decoder.
0812.0038
Omnidirectional Relay in Wireless Networks
cs.IT math.IT
For wireless networks with multiple sources, an omnidirectional relay scheme is developed, where each node can simultaneously relay different messages in different directions. This is accomplished by the decode-and-forward relay strategy, with each relay binning the multiple messages to be transmitted, in the same spirit of network coding. Specially for the all-source all-cast problem, where each node is an independent source to be transmitted to all the other nodes, this scheme completely eliminates interference in the whole network, and the signal transmitted by any node can be used by any other node. For networks with some kind of symmetry, assuming no beamforming is to be performed, this omnidirectional relay scheme is capable of achieving the maximum achievable rate.
0812.0070
An Integrated Software-based Solution for Modular and Self-independent Networked Robot
cs.RO
An integrated software-based solution for a modular and self-independent networked robot is introduced. The wirelessly operatable robot has been developed mainly for autonomous monitoring works with full control over web. The integrated software solution covers three components : a) the digital signal processing unit for data retrieval and monitoring system; b) the externally executable codes for control system; and c) the web programming for interfacing the end-users with the robot. It is argued that this integrated software-based approach is crucial to realize a flexible, modular and low development cost mobile monitoring apparatus.
0812.0319
Secrecy Capacity of a Class of Broadcast Channels with an Eavesdropper
cs.IT math.IT
We study the security of communication between a single transmitter and multiple receivers in a broadcast channel in the presence of an eavesdropper. We consider several special classes of channels. As the first model, we consider the degraded multi-receiver wiretap channel where the legitimate receivers exhibit a degradedness order while the eavesdropper is more noisy with respect to all legitimate receivers. We establish the secrecy capacity region of this channel model. Secondly, we consider the parallel multi-receiver wiretap channel with a less noisiness order in each sub-channel, where this order is not necessarily the same for all sub-channels. We establish the common message secrecy capacity and sum secrecy capacity of this channel. Thirdly, we study a special class of degraded parallel multi-receiver wiretap channels and provide a stronger result. In particular, we study the case with two sub-channels two users and one eavesdropper, where there is a degradedness order in each sub-channel such that in the first (resp. second) sub-channel the second (resp. first) receiver is degraded with respect to the first (resp. second) receiver, while the eavesdropper is degraded with respect to both legitimate receivers in both sub-channels. We determine the secrecy capacity region of this channel. Finally, we focus on a variant of this previous channel model where the transmitter can use only one of the sub-channels at any time. We characterize the secrecy capacity region of this channel as well.
0812.0329
Block-Sparsity: Coherence and Efficient Recovery
cs.IT math.IT
We consider compressed sensing of block-sparse signals, i.e., sparse signals that have nonzero coefficients occuring in clusters. Based on an uncertainty relation for block-sparse signals, we define a block-coherence measure and we show that a block-version of the orthogonal matching pursuit algorithm recovers block k-sparse signals in no more than k steps if the block-coherence is sufficiently small. The same condition on block-sparsity is shown to guarantee successful recovery through a mixed l2/l1 optimization approach. The significance of the results lies in the fact that making explicit use of block-sparsity can yield better reconstruction properties than treating the signal as being sparse in the conventional sense thereby ignoring the additional structure in the problem.
0812.0340
A Matlab Implementation of a Flat Norm Motivated Polygonal Edge Matching Method using a Decomposition of Boundary into Four 1-Dimensional Currents
cs.CV cs.CG
We describe and provide code and examples for a polygonal edge matching method.
0812.0382
k-means requires exponentially many iterations even in the plane
cs.CG cs.DS cs.LG
The k-means algorithm is a well-known method for partitioning n points that lie in the d-dimensional space into k clusters. Its main features are simplicity and speed in practice. Theoretically, however, the best known upper bound on its running time (i.e. O(n^{kd})) can be exponential in the number of points. Recently, Arthur and Vassilvitskii [3] showed a super-polynomial worst-case analysis, improving the best known lower bound from \Omega(n) to 2^{\Omega(\sqrt{n})} with a construction in d=\Omega(\sqrt{n}) dimensions. In [3] they also conjectured the existence of superpolynomial lower bounds for any d >= 2. Our contribution is twofold: we prove this conjecture and we improve the lower bound, by presenting a simple construction in the plane that leads to the exponential lower bound 2^{\Omega(n)}.
0812.0389
Approximation Algorithms for Bregman Co-clustering and Tensor Clustering
cs.DS cs.LG
In the past few years powerful generalizations to the Euclidean k-means problem have been made, such as Bregman clustering [7], co-clustering (i.e., simultaneous clustering of rows and columns of an input matrix) [9,18], and tensor clustering [8,34]. Like k-means, these more general problems also suffer from the NP-hardness of the associated optimization. Researchers have developed approximation algorithms of varying degrees of sophistication for k-means, k-medians, and more recently also for Bregman clustering [2]. However, there seem to be no approximation algorithms for Bregman co- and tensor clustering. In this paper we derive the first (to our knowledge) guaranteed methods for these increasingly important clustering settings. Going beyond Bregman divergences, we also prove an approximation factor for tensor clustering with arbitrary separable metrics. Through extensive experiments we evaluate the characteristics of our method, and show that it also has practical impact.
0812.0438
An Introduction to Knowledge Management
cs.DB cs.CR
Knowledge has been lately recognized as one of the most important assets of organizations. Managing knowledge has grown to be imperative for the success of a company. This paper presents an overview of Knowledge Management and various aspects of secure knowledge management. A case study of knowledge management activities at Tata Steel is also discussed
0812.0564
Provenance Traces
cs.PL cs.DB
Provenance is information about the origin, derivation, ownership, or history of an object. It has recently been studied extensively in scientific databases and other settings due to its importance in helping scientists judge data validity, quality and integrity. However, most models of provenance have been stated as ad hoc definitions motivated by informal concepts such as "comes from", "influences", "produces", or "depends on". These models lack clear formalizations describing in what sense the definitions capture these intuitive concepts. This makes it difficult to compare approaches, evaluate their effectiveness, or argue about their validity. We introduce provenance traces, a general form of provenance for the nested relational calculus (NRC), a core database query language. Provenance traces can be thought of as concrete data structures representing the operational semantics derivation of a computation; they are related to the traces that have been used in self-adjusting computation, but differ in important respects. We define a tracing operational semantics for NRC queries that produces both an ordinary result and a trace of the execution. We show that three pre-existing forms of provenance for the NRC can be extracted from provenance traces. Moreover, traces satisfy two semantic guarantees: consistency, meaning that the traces describe what actually happened during execution, and fidelity, meaning that the traces "explain" how the expression would behave if the input were changed. These guarantees are much stronger than those contemplated for previous approaches to provenance; thus, provenance traces provide a general semantic foundation for comparing and unifying models of provenance in databases.
0812.0617
The Capacity Region of the Cognitive Z-interference Channel with One Noiseless Component
cs.IT math.IT
We study the discrete memoryless Z-interference channel (ZIC) where the transmitter of the pair that suffers from interference is cognitive. We first provide upper and lower bounds on the capacity of this channel. We then show that, when the channel of the transmitter-receiver pair that does not face interference is noiseless, the two bounds coincide and therefore yield the capacity region. The obtained results imply that, unlike in the Gaussian cognitive ZIC, in the considered channel superposition encoding at the non-cognitive transmitter as well as Gel'fand-Pinsker encoding at the cognitive transmitter are needed in order to minimize the impact of interference. As a byproduct of the obtained capacity region, we obtain the capacity result for a generalized Gel'fand-Pinsker problem.
0812.0621
Channel Estimation and Linear Precoding in Multiuser Multiple-Antenna TDD Systems
cs.IT math.IT
Traditional approaches in the analysis of downlink systems decouple the precoding and the channel estimation problems. However, in cellular systems with mobile users, these two problems are in fact tightly coupled. In this paper, this coupling is explicitly studied by accounting for channel training overhead and estimation error while determining the overall system throughput. The paper studies the problem of utilizing imperfect channel estimates for efficient linear precoding and user selection. It presents precoding methods that take into account the degree of channel estimation error. Information-theoretic lower and upper bounds are derived to evaluate the performance of these precoding methods. In typical scenarios, these bounds are close.
0812.0659
Probabilistic reasoning with answer sets
cs.AI cs.LO
This paper develops a declarative language, P-log, that combines logical and probabilistic arguments in its reasoning. Answer Set Prolog is used as the logical foundation, while causal Bayes nets serve as a probabilistic foundation. We give several non-trivial examples and illustrate the use of P-log for knowledge representation and updating of knowledge. We argue that our approach to updates is more appealing than existing approaches. We give sufficiency conditions for the coherency of P-log programs and show that Bayes nets can be easily mapped to coherent P-log programs.
0812.0698
Emergent Community Structure in Social Tagging Systems
cs.IR cs.CY cs.HC
A distributed classification paradigm known as collaborative tagging has been widely adopted in new Web applications designed to manage and share online resources. Users of these applications organize resources (Web pages, digital photographs, academic papers) by associating with them freely chosen text labels, or tags. Here we leverage the social aspects of collaborative tagging and introduce a notion of resource distance based on the collective tagging activity of users. We collect data from a popular system and perform experiments showing that our definition of distance can be used to build a weighted network of resources with a detectable community structure. We show that this community structure clearly exposes the semantic relations among resources. The communities of resources that we observe are a genuinely emergent feature, resulting from the uncoordinated activity of a large number of users, and their detection paves the way for mapping emergent semantics in social tagging systems.
0812.0743
A Novel Clustering Algorithm Based on Quantum Games
cs.LG cs.AI cs.CV cs.GT cs.MA cs.NE quant-ph
Enormous successes have been made by quantum algorithms during the last decade. In this paper, we combine the quantum game with the problem of data clustering, and then develop a quantum-game-based clustering algorithm, in which data points in a dataset are considered as players who can make decisions and implement quantum strategies in quantum games. After each round of a quantum game, each player's expected payoff is calculated. Later, he uses a link-removing-and-rewiring (LRR) function to change his neighbors and adjust the strength of links connecting to them in order to maximize his payoff. Further, algorithms are discussed and analyzed in two cases of strategies, two payoff matrixes and two LRR functions. Consequently, the simulation results have demonstrated that data points in datasets are clustered reasonably and efficiently, and the clustering algorithms have fast rates of convergence. Moreover, the comparison with other algorithms also provides an indication of the effectiveness of the proposed approach.
0812.0759
A new Contrast Based Image Fusion using Wavelet Packets
cs.IT cs.MM math.IT
Image Fusion, a technique which combines complimentary information from different images of the same scene so that the fused image is more suitable for segmentation, feature extraction, object recognition and Human Visual System. In this paper, a simple yet efficient algorithm is presented based on contrast using wavelet packet decomposition. First, all the source images are decomposed into low and high frequency sub-bands and then fusion of high frequency sub-bands is done by the means of Directive Contrast. Now, inverse wavelet packet transform is performed to reconstruct the fused image. The performance of the algorithm is carried out by the comparison made between proposed and existing algorithm.
0812.0790
Justifications for Logic Programs under Answer Set Semantics
cs.AI cs.PL
The paper introduces the notion of off-line justification for Answer Set Programming (ASP). Justifications provide a graph-based explanation of the truth value of an atom w.r.t. a given answer set. The paper extends also this notion to provide justification of atoms during the computation of an answer set (on-line justification), and presents an integration of on-line justifications within the computation model of Smodels. Off-line and on-line justifications provide useful tools to enhance understanding of ASP, and they offer a basic data structure to support methodologies and tools for debugging answer set programs. A preliminary implementation has been developed in ASP-PROLOG. (To appear in Theory and Practice of Logic Programming (TPLP))
0812.0874
Stroke Fragmentation based on Geometry Features and HMM
cs.HC cs.CV
Stroke fragmentation is one of the key steps in pen-based interaction. In this letter, we present a unified HMM-based stroke fragmentation technique that can do segment point location and primitive type determination simultaneously. The geometry features included are used to evaluate local features, and the HMM model is utilized to measure the global drawing context. Experiments prove that the model can efficiently represent smooth curves as well as strokes made up of arbitrary lines and circular arcs.
0812.0882
Elagage d'un perceptron multicouches : utilisation de l'analyse de la variance de la sensibilit\'e des param\`etres
cs.NE
The stucture determination of a neural network for the modelisation of a system remain the core of the problem. Within this framework, we propose a pruning algorithm of the network based on the use of the analysis of the sensitivity of the variance of all the parameters of the network. This algorithm will be tested on two examples of simulation and its performances will be compared with three other algorithms of pruning of the literature
0812.0885
Elementary epistemological features of machine intelligence
cs.AI
Theoretical analysis of machine intelligence (MI) is useful for defining a common platform in both theoretical and applied artificial intelligence (AI). The goal of this paper is to set canonical definitions that can assist pragmatic research in both strong and weak AI. Described epistemological features of machine intelligence include relationship between intelligent behavior, intelligent and unintelligent machine characteristics, observable and unobservable entities and classification of intelligence. The paper also establishes algebraic definitions of efficiency and accuracy of MI tests as their quality measure. The last part of the paper addresses the learning process with respect to the traditional epistemology and the epistemology of MI described here. The proposed views on MI positively correlate to the Hegelian monistic epistemology and contribute towards amalgamating idealistic deliberations with the AI theory, particularly in a local frame of reference.
0812.0933
Decision trees are PAC-learnable from most product distributions: a smoothed analysis
cs.LG cs.CC
We consider the problem of PAC-learning decision trees, i.e., learning a decision tree over the n-dimensional hypercube from independent random labeled examples. Despite significant effort, no polynomial-time algorithm is known for learning polynomial-sized decision trees (even trees of any super-constant size), even when examples are assumed to be drawn from the uniform distribution on {0,1}^n. We give an algorithm that learns arbitrary polynomial-sized decision trees for {\em most product distributions}. In particular, consider a random product distribution where the bias of each bit is chosen independently and uniformly from, say, [.49,.51]. Then with high probability over the parameters of the product distribution and the random examples drawn from it, the algorithm will learn any tree. More generally, in the spirit of smoothed analysis, we consider an arbitrary product distribution whose parameters are specified only up to a [-c,c] accuracy (perturbation), for an arbitrarily small positive constant c.
0812.0972
Network Protection Codes: Providing Self-healing in Autonomic Networks Using Network Coding
cs.NI cs.IT math.IT
Agile recovery from link failures in autonomic communication networks is essential to increase robustness, accessibility, and reliability of data transmission. However, this must be done with the least amount of protection resources, while using simple management plane functionality. Recently, network coding has been proposed as a solution to provide agile and cost efficient network self-healing against link failures, in a manner that does not require data rerouting, packet retransmission, or failure localization, hence leading to simple control and management planes. To achieve this, separate paths have to be provisioned to carry encoded packets, hence requiring either the addition of extra links, or reserving some of the resources for this purpose. In this paper we introduce autonomic self-healing strategies for autonomic networks in order to protect against link failures. The strategies are based on network coding and reduced capacity, which is a technique that we call network protection codes (NPC). In these strategies, an autonomic network is able to provide self-healing from various network failures affecting network operation. The techniques improve service and enhance reliability of autonomic communication. Network protection codes are extended to provide self-healing from multiple link failures in autonomic networks. We provide implementation aspects of the proposed strategies. We present bounds and network protection code constructions. Finally, we study the construction of such codes over the binary field. The paper also develops an Integer Linear Program formulation to evaluate the cost of provisioning connections using the proposed strategies.
0812.1014
Adaptive Spam Detection Inspired by a Cross-Regulation Model of Immune Dynamics: A Study of Concept Drift
cs.AI cs.IR nlin.AO
This paper proposes a novel solution to spam detection inspired by a model of the adaptive immune system known as the crossregulation model. We report on the testing of a preliminary algorithm on six e-mail corpora. We also compare our results statically and dynamically with those obtained by the Naive Bayes classifier and another binary classification method we developed previously for biomedical text-mining applications. We show that the cross-regulation model is competitive against those and thus promising as a bio-inspired algorithm for spam detection in particular, and binary classification in general.
0812.1029
Uncovering protein interaction in abstracts and text using a novel linear model and word proximity networks
cs.IR cs.LG
We participated in three of the protein-protein interaction subtasks of the Second BioCreative Challenge: classification of abstracts relevant for protein-protein interaction (IAS), discovery of protein pairs (IPS) and text passages characterizing protein interaction (ISS) in full text documents. We approached the abstract classification task with a novel, lightweight linear model inspired by spam-detection techniques, as well as an uncertainty-based integration scheme. We also used a Support Vector Machine and the Singular Value Decomposition on the same features for comparison purposes. Our approach to the full text subtasks (protein pair and passage identification) includes a feature expansion method based on word-proximity networks. Our approach to the abstract classification task (IAS) was among the top submissions for this task in terms of the measures of performance used in the challenge evaluation (accuracy, F-score and AUC). We also report on a web-tool we produced using our approach: the Protein Interaction Abstract Relevance Evaluator (PIARE). Our approach to the full text tasks resulted in one of the highest recall rates as well as mean reciprocal rank of correct passages. Our approach to abstract classification shows that a simple linear model, using relatively few features, is capable of generalizing and uncovering the conceptual nature of protein-protein interaction from the bibliome. Since the novel approach is based on a very lightweight linear model, it can be easily ported and applied to similar problems. In full text problems, the expansion of word features with word-proximity networks is shown to be useful, though the need for some improvements is discussed.
0812.1091
Communicating the Difference of Correlated Gaussian Sources Over a MAC
cs.IT math.IT
This paper considers the problem of transmitting the difference of two jointly Gaussian sources over a two-user additive Gaussian noise multiple access channel (MAC). The goal is to recover this difference within an average mean squared error distortion criterion. Each transmitter has access to only one of the two Gaussian sources and is limited by an average power constraint. In this work, a lattice coding scheme that achieves a distortion within a constant of a distortion lower bound is presented if the signal to noise ratio (SNR) is greater than a threshold. Further, uncoded transmission is shown to be worse in performance to lattice coding methods. An alternative lattice coding scheme is presented that can potentially improve on the performance of uncoded transmission.
0812.1094
S\'election de la structure d'un perceptron multicouches pour la r\'eduction dun mod\`ele de simulation d'une scierie
cs.NE
Simulation is often used to evaluate the relevance of a Directing Program of Production (PDP) or to evaluate its impact on detailed sc\'enarii of scheduling. Within this framework, we propose to reduce the complexity of a model of simulation by exploiting a multilayer perceptron. A main phase of the modeling of one system using a multilayer perceptron remains the determination of the structure of the network. We propose to compare and use various pruning algorithms in order to determine the optimal structure of the network used to reduce the complexity of the model of simulation of our case of application: a sawmill.
0812.1119
An analysis of a random algorithm for estimating all the matchings
cs.GR cs.AI
Counting the number of all the matchings on a bipartite graph has been transformed into calculating the permanent of a matrix obtained from the extended bipartite graph by Yan Huo, and Rasmussen presents a simple approach (RM) to approximate the permanent, which just yields a critical ratio O($n\omega(n)$) for almost all the 0-1 matrices, provided it's a simple promising practical way to compute this #P-complete problem. In this paper, the performance of this method will be shown when it's applied to compute all the matchings based on that transformation. The critical ratio will be proved to be very large with a certain probability, owning an increasing factor larger than any polynomial of $n$ even in the sense for almost all the 0-1 matrices. Hence, RM fails to work well when counting all the matchings via computing the permanent of the matrix. In other words, we must carefully utilize the known methods of estimating the permanent to count all the matchings through that transformation.
0812.1126
Emerge-Sort: Converging to Ordered Sequences by Simple Local Operators
cs.AI cs.DS
In this paper we examine sorting on the assumption that we do not know in advance which way to sort a sequence of numbers and we set at work simple local comparison and swap operators whose repeating application ends up in sorted sequences. These are the basic elements of Emerge-Sort, our approach to self-organizing sorting, which we then validate experimentally across a range of samples. Observing an O(n2) run-time behaviour, we note that the n/logn delay coefficient that differentiates Emerge-Sort from the classical comparison based algorithms is an instantiation of the price of anarchy we pay for not imposing a sorting order and for letting that order emerge through the local interactions.
0812.1155
Complex Agent Networks explaining the HIV epidemic among homosexual men in Amsterdam
cs.MA q-bio.PE
Simulating the evolution of the Human Immunodeficiency Virus (HIV) epidemic requires a detailed description of the population network, especially for small populations in which individuals can be represented in detail and accuracy. In this paper, we introduce the concept of a Complex Agent Network(CAN) to model the HIV epidemics by combining agent-based modelling and complex networks, in which agents represent individuals that have sexual interactions. The applicability of CANs is demonstrated by constructing and executing a detailed HIV epidemic model for men who have sex with men (MSM) in Amsterdam, including a distinction between steady and casual relationships. We focus on MSM contacts because they play an important role in HIV epidemics and have been tracked in Amsterdam for a long time. Our experiments show good correspondence between the historical data of the Amsterdam cohort and the simulation results.
0812.1203
An Efficient Adaptive Distributed Space-Time Coding Scheme for Cooperative Relaying
cs.IT math.IT
A non-regenerative dual-hop wireless system based on a distributed space-time coding strategy is considered. It is assumed that each relay retransmits an appropriately scaled space-time coded version of its received signal. The main goal of this paper is to investigate a power allocation strategy in relay stations, which is based on minimizing the outage probability. In the high signal-to-noise ratio regime for the relay-destination link, it is shown that a threshold-based power allocation scheme (i.e., the relay remains silent if its channel gain with the source is less than a prespecified threshold) is optimum. Monte-Carlo simulations show that the derived on-off power allocation scheme performs close to optimum for finite signal-to-noise ratio values. Numerical results demonstrate a dramatic improvement in system performance as compared to the case that the relay stations forward their received signals with full power. In addition, a hybrid amplify-and-forward/detect-and-forward scheme is proposed for the case that the quality of the source-relay link is good. Finally, the robustness of the proposed scheme in the presence of channel estimation errors is numerically evaluated.
0812.1244
Decomposition Principles and Online Learning in Cross-Layer Optimization for Delay-Sensitive Applications
cs.MM cs.LG
In this paper, we propose a general cross-layer optimization framework in which we explicitly consider both the heterogeneous and dynamically changing characteristics of delay-sensitive applications and the underlying time-varying network conditions. We consider both the independently decodable data units (DUs, e.g. packets) and the interdependent DUs whose dependencies are captured by a directed acyclic graph (DAG). We first formulate the cross-layer design as a non-linear constrained optimization problem by assuming complete knowledge of the application characteristics and the underlying network conditions. The constrained cross-layer optimization is decomposed into several cross-layer optimization subproblems for each DU and two master problems. The proposed decomposition method determines the necessary message exchanges between layers for achieving the optimal cross-layer solution. However, the attributes (e.g. distortion impact, delay deadline etc) of future DUs as well as the network conditions are often unknown in the considered real-time applications. The impact of current cross-layer actions on the future DUs can be characterized by a state-value function in the Markov decision process (MDP) framework. Based on the dynamic programming solution to the MDP, we develop a low-complexity cross-layer optimization algorithm using online learning for each DU transmission. This online algorithm can be implemented in real-time in order to cope with unknown source characteristics, network dynamics and resource constraints. Our numerical results demonstrate the efficiency of the proposed online algorithm.
0812.1340
Obtaining Depth Maps From Color Images By Region Based Stereo Matching Algorithms
cs.CV
In the paper, region based stereo matching algorithms are developed for extraction depth information from two color stereo image pair. A filter eliminating unreliable disparity estimation was used for increasing reliability of the disparity map. Obtained results by algorithms were represented and compared.
0812.1357
A Novel Clustering Algorithm Based on Quantum Random Walk
cs.LG
The enormous successes have been made by quantum algorithms during the last decade. In this paper, we combine the quantum random walk (QRW) with the problem of data clustering, and develop two clustering algorithms based on the one dimensional QRW. Then, the probability distributions on the positions induced by QRW in these algorithms are investigated, which also indicates the possibility of obtaining better results. Consequently, the experimental results have demonstrated that data points in datasets are clustered reasonably and efficiently, and the clustering algorithms are of fast rates of convergence. Moreover, the comparison with other algorithms also provides an indication of the effectiveness of the proposed approach.
0812.1394
Conceptual approach through an annotation process for the representation and the information contents enhancement in economic intelligence (EI)
cs.IR
In the era of the information society, the impact of the information systems on the economy of material and immaterial is certainly perceptible. With regards to the information resources of an organization, the annotation involved to enrich informational content, to track the intellectual activities on a document and to set the added value on information for the benefit of solving a decision-making problem in the context of economic intelligence. Our contribution is distinguished by the representation of an annotation process and its inherent concepts to lead the decisionmaker to an anticipated decision: the provision of relevant and annotated information. Such information in the system is made easy by taking into account the diversity of resources and those that are well annotated so formally and informally by the EI actors. A capital research framework consist of integrating in the decision-making process the annotator activity, the software agent (or the reasoning mechanisms) and the information resources enhancement.
0812.1405
Cognitive Coexistence between Infrastructure and Ad-hoc Systems
cs.IT math.IT
The rapid proliferation of wireless systems makes interference management more and more important. This paper presents a novel cognitive coexistence framework, which enables an infrastructure system to reduce interference to ad-hoc or peer-to-peer communication links in close proximity. Motivated by the superior resources of the infrastructure system, we study how its centralized resource allocation can accommodate the ad-hoc links based on sensing and predicting their interference patterns. Based on an ON/OFF continuous-time Markov chain model, the optimal allocation of power and transmission time is formulated as a convex optimization problem and closed-form solutions are derived. The optimal scheduling is extended to the case where the infrastructure channel is random and rate constraints need only be met in the long-term average. Finally, the multi-terminal case is addressed and the problem of optimal sub-channel allocation discussed. Numerical performance analysis illustrates that utilizing the superior flexibility of the infrastructure links can effectively mitigate interference.
0812.1462
Logic programs with propositional connectives and aggregates
cs.AI
Answer set programming (ASP) is a logic programming paradigm that can be used to solve complex combinatorial search problems. Aggregates are an ASP construct that plays an important role in many applications. Defining a satisfactory semantics of aggregates turned out to be a difficult problem, and in this paper we propose a new approach, based on an analogy between aggregates and propositional connectives. First, we extend the definition of an answer set/stable model to cover arbitrary propositional theories; then we define aggregates on top of them both as primitive constructs and as abbreviations for formulas. Our definition of an aggregate combines expressiveness and simplicity, and it inherits many theorems about programs with nested expressions, such as theorems about strong equivalence and splitting.
0812.1553
Analysis of Energy Efficiency in Fading Channels under QoS Constraints
cs.IT math.IT
Energy efficiency in fading channels in the presence of Quality of Service (QoS) constraints is studied. Effective capacity, which provides the maximum arrival rate that a wireless channel can sustain while satisfying statistical QoS constraints, is considered. Spectral efficiency--bit energy tradeoff is analyzed in the low-power and wideband regimes by employing the effective capacity formulation, rather than the Shannon capacity. Through this analysis, energy requirements under QoS constraints are identified. The analysis is conducted under two assumptions: perfect channel side information (CSI) available only at the receiver and perfect CSI available at both the receiver and transmitter. In particular, it is shown in the low-power regime that the minimum bit energy required under QoS constraints is the same as that attained when there are no such limitations. However, this performance is achieved as the transmitted power vanishes. Through the wideband slope analysis, the increased energy requirements at low but nonzero power levels in the presence of QoS constraints are determined. A similar analysis is also conducted in the wideband regime, and minimum bit energy and wideband slope expressions are obtained. In this regime, the required bit energy levels are found to be strictly greater than those achieved when Shannon capacity is considered. Overall, a characterization of the energy-bandwidth-delay tradeoff is provided.
0812.1554
Molecular communication: Physically realistic models and achievable information rates
cs.IT math.IT
Molecular communication is a biologically-inspired method of communication with attractive properties for microscale and nanoscale devices. In molecular communication, messages are transmitted by releasing a pattern of molecules at a transmitter, which propagate through a fluid medium towards a receiver. In this paper, molecular communication is formulated as a mathematical communication problem in an information-theoretic context. Physically realistic models are obtained, with sufficient abstraction to allow manipulation by communication and information theorists. Although mutual information in these channels is intractable, we give sequences of upper and lower bounds on the mutual information which trade off complexity and performance, and present results to illustrate the feasibility of these bounds in estimating the true mutual information.
0812.1557
To Cooperate, or Not to Cooperate in Imperfectly-Known Fading Channels
cs.IT math.IT
In this paper, communication over imperfectly-known fading channels with different degrees of cooperation is studied. The three-node relay channel is considered. It is assumed that communication starts with the network training phase in which the receivers estimate the fading coefficients of their respective channels. In the data transmission phase, amplify-and-forward and decode-and-forward relaying schemes are employed. For different cooperation protocols, achievable rate expressions are obtained. These achievable rate expressions are then used to find the optimal resource allocation strategies. In particular, the fraction of total time or bandwidth that needs to be allocated to the relay for best performance is identified. Under a total power constraint, optimal allocation of power between the source and relay is investigated. Finally, bit energy requirements in the low-power regime are studied.
0812.1558
Pilot-Symbol-Assisted Communications with Noncausal and Causal Wiener Filters
cs.IT math.IT
In this paper, pilot-assisted transmission over time-selective flat fading channels is studied. It is assumed that noncausal and causal Wiener filters are employed at the receiver to perform channel estimation with the aid of training symbols sent periodically by the transmitter. For both filters, the variances of estimate errors are obtained from the Doppler power spectrum of the channel. Subsequently, achievable rate expressions are provided. The training period, and data and training power allocations are jointly optimized by maximizing the achievable rate expressions. Numerical results are obtained by modeling the fading as a Gauss-Markov process. The achievable rates of causal and noncausal filtering approaches are compared. For the particular ranges of parameters considered in the paper, the performance loss incurred by using a causal filter as opposed to a noncausal filter is shown to be small. The impact of aliasing that occurs in the undersampled version of the channel Doppler spectrum due to fast fading is analyzed. Finally, energy-per-bit requirements are investigated in the presence of noncausal and causal Wiener filters.
0812.1560
Achievable Rates and Training Optimization for Fading Relay Channels with Memory
cs.IT math.IT
In this paper, transmission over time-selective, flat fading relay channels is studied. It is assumed that channel fading coefficients are not known a priori. Transmission takes place in two phases: network training phase and data transmission phase. In the training phase, pilot symbols are sent and the receivers employ single-pilot MMSE estimation or noncausal Wiener filter to learn the channel. Amplify-and-Forward (AF) and Decode-and-Forward (DF) techniques are considered in the data transmission phase and achievable rate expressions are obtained. The training period, and data and training power allocations are jointly optimized by using the achievable rate expressions. Numerical results are obtained considering Gauss-Markov and lowpass fading models. Achievable rates are computed and energy-per-bit requirements are investigated. The optimal power distributions among pilot and data symbols are provided.
0812.1597
Transmission Techniques for Relay-Interference Networks
cs.IT math.IT
In this paper we study the relay-interference wireless network, in which relay (helper) nodes are to facilitate competing information flows over a wireless network. We examine this in the context of a deterministic wireless interaction model, which eliminates the channel noise and focuses on the signal interactions. Using this model, we show that almost all the known schemes such as interference suppression, interference alignment and interference separation are necessary for relay-interference networks. In addition, we discover a new interference management technique, which we call interference neutralization, which allows for over-the-air interference removal, without the transmitters having complete access the interfering signals. We show that interference separation, suppression, and neutralization arise in a fundamental manner, since we show complete characterizations for special configurations of the relay-interference network.
0812.1599
Multi-Agent Reinforcement Learning and Genetic Policy Sharing
cs.MA cs.AI
The effects of policy sharing between agents in a multi-agent dynamical system has not been studied extensively. I simulate a system of agents optimizing the same task using reinforcement learning, to study the effects of different population densities and policy sharing. I demonstrate that sharing policies decreases the time to reach asymptotic behavior, and results in improved asymptotic behavior.
0812.1629
An application of the O'Nan-Scott theorem to the group generated by the round functions of an AES-like cipher
math.GR cs.IT math.IT
In a previous paper, we had proved that the permutation group generated by the round functions of an AES-like cipher is primitive. Here we apply the O'Nan Scott classification of primitive groups to prove that this group is the alternating group.
0812.1713
Secret Communication with Feedback
cs.IT math.IT
Secure communication with feedback is studied. An achievability scheme in which the backward channel is used to generate a shared secret key is proposed. The scenario of binary symmetric forward and backward channels is considered, and a combination of the proposed scheme and Maurer's coding scheme is shown to achieve improved secrecy rates. The scenario of a Gaussian channel with perfect output feedback is also analyzed and the Schalkwijk-Kailath coding scheme is shown to achieve the secrecy capacity for this channel.
0812.1778
The Impact of QoS Constraints on the Energy Efficiency of Fixed-Rate Wireless Transmissions
cs.IT math.IT
Transmission over wireless fading channels under quality of service (QoS) constraints is studied when only the receiver has channel side information. Being unaware of the channel conditions, transmitter is assumed to send the information at a fixed rate. Under these assumptions, a two-state (ON-OFF) transmission model is adopted, where information is transmitted reliably at a fixed rate in the ON state while no reliable transmission occurs in the OFF state. QoS limitations are imposed as constraints on buffer violation probabilities, and effective capacity formulation is used to identify the maximum throughput that a wireless channel can sustain while satisfying statistical QoS constraints. Energy efficiency is investigated by obtaining the bit energy required at zero spectral efficiency and the wideband slope in both wideband and low-power regimes assuming that the receiver has perfect channel side information (CSI). In both wideband and low-power regimes, the increased energy requirements due to the presence of QoS constraints are quantified. Comparisons with variable-rate/fixed-power and variable-rate/variable-power cases are given. Energy efficiency is further analyzed in the presence of channel uncertainties. The optimal fraction of power allocated to training is identified under QoS constraints. It is proven that the minimum bit energy in the low-power regime is attained at a certain nonzero power level below which bit energy increases without bound with vanishing power.
0812.1780
On the Energy Efficiency of Orthogonal Signaling
cs.IT math.IT
In this paper, transmission over the additive white Gaussian noise (AWGN) channel, and coherent and noncoherent fading channels using M-ary orthogonal frequency-shift keying (FSK) or on-off frequency-shift keying (OOFSK) is considered. The receiver is assumed to perform hard-decision detection. In this setting, energy required to reliably send one bit of information is investigated. It is shown that for fixed M and duty cycle, bit energy requirements grow without bound as the signal-to-noise ratio (SNR) vanishes. The minimum bit energy values are numerically obtained for different values of M and the duty cycle. The impact of fading on the energy efficiency is identified. Requirements to approach the minimum bit energy of -1.59 dB are determined.
0812.1811
Stability of graph communities across time scales
physics.soc-ph cs.IR physics.data-an
The complexity of biological, social and engineering networks makes it desirable to find natural partitions into communities that can act as simplified descriptions and provide insight into the structure and function of the overall system. Although community detection methods abound, there is a lack of consensus on how to quantify and rank the quality of partitions. We show here that the quality of a partition can be measured in terms of its stability, defined in terms of the clustered autocovariance of a Markov process taking place on the graph. Because the stability has an intrinsic dependence on time scales of the graph, it allows us to compare and rank partitions at each time and also to establish the time spans over which partitions are optimal. Hence the Markov time acts effectively as an intrinsic resolution parameter that establishes a hierarchy of increasingly coarser clusterings. Within our framework we can then provide a unifying view of several standard partitioning measures: modularity and normalized cut size can be interpreted as one-step time measures, whereas Fiedler's spectral clustering emerges at long times. We apply our method to characterize the relevance and persistence of partitions over time for constructive and real networks, including hierarchical graphs and social networks. We also obtain reduced descriptions for atomic level protein structures over different time scales.
0812.1843
Identification of parameters underlying emotions and a classification of emotions
cs.AI
The standard classification of emotions involves categorizing the expression of emotions. In this paper, parameters underlying some emotions are identified and a new classification based on these parameters is suggested.
0812.1857
Dependence Balance Based Outer Bounds for Gaussian Networks with Cooperation and Feedback
cs.IT math.IT
We obtain new outer bounds on the capacity regions of the two-user multiple access channel with generalized feedback (MAC-GF) and the two-user interference channel with generalized feedback (IC-GF). These outer bounds are based on the idea of dependence balance which was proposed by Hekstra and Willems [1]. To illustrate the usefulness of our outer bounds, we investigate three different channel models. We first consider a Gaussian MAC with noisy feedback (MAC-NF), where transmitter $k$, $k=1,2$, receives a feedback $Y_{F_{k}}$, which is the channel output $Y$ corrupted with additive white Gaussian noise $Z_{k}$. As the feedback noise variances become large, one would expect the feedback to become useless, which is not reflected by the cut-set bound. We demonstrate that our outer bound improves upon the cut-set bound for all non-zero values of the feedback noise variances. Moreover, in the limit as $\sigma_{Z_{k}}^{2}\to \infty$, $k=1,2$, our outer bound collapses to the capacity region of the Gaussian MAC without feedback. Secondly, we investigate a Gaussian MAC with user-cooperation (MAC-UC), where each transmitter receives an additive white Gaussian noise corrupted version of the channel input of the other transmitter [2]. For this channel model, the cut-set bound is sensitive to the cooperation noises, but not sensitive enough. For all non-zero values of cooperation noise variances, our outer bound strictly improves upon the cut-set outer bound. Thirdly, we investigate a Gaussian IC with user-cooperation (IC-UC). For this channel model, the cut-set bound is again sensitive to cooperation noise variances but not sensitive enough. We demonstrate that our outer bound strictly improves upon the cut-set bound for all non-zero values of cooperation noise variances.
0812.1869
Convex Sparse Matrix Factorizations
cs.LG
We present a convex formulation of dictionary learning for sparse signal decomposition. Convexity is obtained by replacing the usual explicit upper bound on the dictionary size by a convex rank-reducing term similar to the trace norm. In particular, our formulation introduces an explicit trade-off between size and sparsity of the decomposition of rectangular matrices. Using a large set of synthetic examples, we compare the estimation abilities of the convex and non-convex approaches, showing that while the convex formulation has a single local minimum, this may lead in some cases to performance which is inferior to the local minima of the non-convex formulation.
0812.2049
Consensus Answers for Queries over Probabilistic Databases
cs.DB
We address the problem of finding a "best" deterministic query answer to a query over a probabilistic database. For this purpose, we propose the notion of a consensus world (or a consensus answer) which is a deterministic world (answer) that minimizes the expected distance to the possible worlds (answers). This problem can be seen as a generalization of the well-studied inconsistent information aggregation problems (e.g. rank aggregation) to probabilistic databases. We consider this problem for various types of queries including SPJ queries, \Topk queries, group-by aggregate queries, and clustering. For different distance metrics, we obtain polynomial time optimal or approximation algorithms for computing the consensus answers (or prove NP-hardness). Most of our results are for a general probabilistic database model, called {\em and/xor tree model}, which significantly generalizes previous probabilistic database models like x-tuples and block-independent disjoint models, and is of independent interest.
0812.2195
Equivalence of SQL Queries in Presence of Embedded Dependencies
cs.DB
We consider the problem of finding equivalent minimal-size reformulations of SQL queries in presence of embedded dependencies [1]. Our focus is on select-project-join (SPJ) queries with equality comparisons, also known as safe conjunctive (CQ) queries, possibly with grouping and aggregation. For SPJ queries, the semantics of the SQL standard treat query answers as multisets (a.k.a. bags), whereas the stored relations may be treated either as sets, which is called bag-set semantics for query evaluation, or as bags, which is called bag semantics. (Under set semantics, both query answers and stored relations are treated as sets.) In the context of the above Query-Reformulation Problem, we develop a comprehensive framework for equivalence of CQ queries under bag and bag-set semantics in presence of embedded dependencies, and make a number of conceptual and technical contributions. Specifically, we develop equivalence tests for CQ queries in presence of arbitrary sets of embedded dependencies under bag and bag-set semantics, under the condition that chase [9] under set semantics (set-chase) on the inputs terminates. We also present equivalence tests for aggregate CQ queries in presence of embedded dependencies. We use our equivalence tests to develop sound and complete (whenever set-chase on the inputs terminates) algorithms for solving instances of the Query-Reformulation Problem with CQ queries under each of bag and bag-set semantics, as well as for instances of the problem with aggregate queries.
0812.2202
Greedy Signal Recovery Review
math.NA cs.IT math.IT
The two major approaches to sparse recovery are L1-minimization and greedy methods. Recently, Needell and Vershynin developed Regularized Orthogonal Matching Pursuit (ROMP) that has bridged the gap between these two approaches. ROMP is the first stable greedy algorithm providing uniform guarantees. Even more recently, Needell and Tropp developed the stable greedy algorithm Compressive Sampling Matching Pursuit (CoSaMP). CoSaMP provides uniform guarantees and improves upon the stability bounds and RIC requirements of ROMP. CoSaMP offers rigorous bounds on computational cost and storage. In many cases, the running time is just O(NlogN), where N is the ambient dimension of the signal. This review summarizes these major advances.
0812.2275
Secrecy capacity of a class of orthogonal relay eavesdropper channels
cs.IT math.IT
The secrecy capacity of relay channels with orthogonal components is studied in the presence of an additional passive eavesdropper node. The relay and destination receive signals from the source on two orthogonal channels such that the destination also receives transmissions from the relay on its channel. The eavesdropper can overhear either one or both of the orthogonal channels. Inner and outer bounds on the secrecy capacity are developed for both the discrete memoryless and the Gaussian channel models. For the discrete memoryless case, the secrecy capacity is shown to be achieved by a partial decode-and-forward (PDF) scheme when the eavesdropper can overhear only one of the two orthogonal channels. Two new outer bounds are presented for the Gaussian model using recent capacity results for a Gaussian multi-antenna point-to-point channel with a multi-antenna eavesdropper. The outer bounds are shown to be tight for two sub-classes of channels. The first sub-class is one in which the source and relay are clustered and the and the eavesdropper receives signals only on the channel from the source and the relay to the destination, for which the PDF strategy is optimal. The second is a sub-class in which the source does not transmit to the relay, for which a noise-forwarding strategy is optimal.
0812.2291
Characterizing Truthful Multi-Armed Bandit Mechanisms
cs.DS cs.GT cs.LG
We consider a multi-round auction setting motivated by pay-per-click auctions for Internet advertising. In each round the auctioneer selects an advertiser and shows her ad, which is then either clicked or not. An advertiser derives value from clicks; the value of a click is her private information. Initially, neither the auctioneer nor the advertisers have any information about the likelihood of clicks on the advertisements. The auctioneer's goal is to design a (dominant strategies) truthful mechanism that (approximately) maximizes the social welfare. If the advertisers bid their true private values, our problem is equivalent to the "multi-armed bandit problem", and thus can be viewed as a strategic version of the latter. In particular, for both problems the quality of an algorithm can be characterized by "regret", the difference in social welfare between the algorithm and the benchmark which always selects the same "best" advertisement. We investigate how the design of multi-armed bandit algorithms is affected by the restriction that the resulting mechanism must be truthful. We find that truthful mechanisms have certain strong structural properties -- essentially, they must separate exploration from exploitation -- and they incur much higher regret than the optimal multi-armed bandit algorithms. Moreover, we provide a truthful mechanism which (essentially) matches our lower bound on regret.
0812.2301
Cooperative Hybrid ARQ Protocols: Unified Frameworks for Protocol Analysis
cs.IT math.IT
Cooperative hybrid-ARQ (HARQ) protocols, which can exploit the spatial and temporal diversities, have been widely studied. The efficiency of cooperative HARQ protocols is higher than that of cooperative protocols, because retransmissions are only performed when necessary. We classify cooperative HARQ protocols as three decode-and-forward based HARQ (DF-HARQ) protocols and two amplified-and-forward based (AF-HARQ) protocols. To compare these protocols and obtain the optimum parameters, two unified frameworks are developed for protocol analysis. Using the frameworks, we can evaluate and compare the maximum throughput and outage probabilities according to the SNR, the relay location, and the delay constraint for the protocols.
0812.2309
Classification of Cell Images Using MPEG-7-influenced Descriptors and Support Vector Machines in Cell Morphology
stat.AP cs.CV stat.ML
Counting and classifying blood cells is an important diagnostic tool in medicine. Support Vector Machines are increasingly popular and efficient and could replace artificial neural network systems. Here a method to classify blood cells is proposed using SVM. A set of statistics on images are implemented in C++. The MPEG-7 descriptors Scalable Color Descriptor, Color Structure Descriptor, Color Layout Descriptor and Homogeneous Texture Descriptor are extended in size and combined with textural features corresponding to textural properties perceived visually by humans. From a set of images of human blood cells these statistics are collected. A SVM is implemented and trained to classify the cell images. The cell images come from a CellaVision DM-96 machine which classify cells from images from microscopy. The output images and classification of the CellaVision machine is taken as ground truth, a truth that is 90-95% correct. The problem is divided in two -- the primary and the simplified. The primary problem is to classify the same classes as the CellaVision machine. The simplified problem is to differ between the five most common types of white blood cells. An encouraging result is achieved in both cases -- error rates of 10.8% and 3.1% -- considering that the SVM is misled by the errors in ground truth. Conclusion is that further investigation of performance is worthwhile.
0812.2313
Urologic robots and future directions
cs.RO
PURPOSE OF REVIEW: Robot-assisted laparoscopic surgery in urology has gained immense popularity with the daVinci system, but a lot of research teams are working on new robots. The purpose of this study is to review current urologic robots and present future development directions. RECENT FINDINGS: Future systems are expected to advance in two directions: improvements of remote manipulation robots and developments of image-guided robots. SUMMARY: The final goal of robots is to allow safer and more homogeneous outcomes with less variability of surgeon performance, as well as new tools to perform tasks on the basis of medical transcutaneous imaging, in a less invasive way, at lower costs. It is expected that improvements for a remote system could be augmented in reality, with haptic feedback, size reduction, and development of new tools for natural orifice translumenal endoscopic surgery. The paradigm of image-guided robots is close to clinical availability and the most advanced robots are presented with end-user technical assessments. It is also notable that the potential of robots lies much further ahead than the accomplishments of the daVinci system. The integration of imaging with robotics holds a substantial promise, because this can accomplish tasks otherwise impossible. Image-guided robots have the potential to offer a paradigm shift.
0812.2324
The MIMO Iterative Waterfilling Algorithm
cs.IT cs.GT math.IT
This paper considers the non-cooperative maximization of mutual information in the vector Gaussian interference channel in a fully distributed fashion via game theory. This problem has been widely studied in a number of works during the past decade for frequency-selective channels, and recently for the more general MIMO case, for which the state-of-the art results are valid only for nonsingular square channel matrices. Surprisingly, these results do not hold true when the channel matrices are rectangular and/or rank deficient matrices. The goal of this paper is to provide a complete characterization of the MIMO game for arbitrary channel matrices, in terms of conditions guaranteeing both the uniqueness of the Nash equilibrium and the convergence of asynchronous distributed iterative waterfilling algorithms. Our analysis hinges on new technical intermediate results, such as a new expression for the MIMO waterfilling projection valid (also) for singular matrices, a mean-value theorem for complex matrix-valued functions, and a general contraction theorem for the multiuser MIMO watefilling mapping valid for arbitrary channel matrices. The quite surprising result is that uniqueness/convergence conditions in the case of tall (possibly singular) channel matrices are more restrictive than those required in the case of (full rank) fat channel matrices. We also propose a modified game and algorithm with milder conditions for the uniqueness of the equilibrium and convergence, and virtually the same performance (in terms of Nash equilibria) of the original game.
0812.2379
On the Decoder Error Probability of Rank Metric Codes and Constant-Dimension Codes
cs.IT math.IT
Rank metric codes and constant-dimension codes (CDCs) have been considered for error control in random network coding. Since decoder errors are more detrimental to system performance than decoder failures, in this paper we investigate the decoder error probability (DEP) of bounded distance decoders (BDDs) for rank metric codes and CDCs. For rank metric codes, we consider a channel motivated by network coding, where errors with the same row space are equiprobable. Over such channels, we establish upper bounds on the DEPs of BDDs, determine the exact DEP of BDDs for maximum rank distance (MRD) codes, and show that MRD codes have the greatest DEPs up to a scalar. To evaluate the DEPs of BDDs for CDCs, we first establish some fundamental geometric properties of the projective space. Using these geometric properties, we then consider BDDs in both subspace and injection metrics and derive analytical expressions of their DEPs for CDCs, over a symmetric operator channel, as functions of their distance distributions. Finally, we focus on CDCs obtained by lifting rank metric codes and establish two important results: First, we derive asymptotically tight upper bounds on the DEPs of BDDs in both metrics; Second, we show that the DEPs for KK codes are the greatest up to a scalar among all CDCs obtained by lifting rank metric codes.
0812.2388
Physics of risk and uncertainty in quantum decision making
physics.soc-ph cs.AI quant-ph
The Quantum Decision Theory, developed recently by the authors, is applied to clarify the role of risk and uncertainty in decision making and in particular in relation to the phenomenon of dynamic inconsistency. By formulating this notion in precise mathematical terms, we distinguish three types of inconsistency: time inconsistency, planning paradox, and inconsistency occurring in some discounting effects. While time inconsistency is well accounted for in classical decision theory, the planning paradox is in contradiction with classical utility theory. It finds a natural explanation in the frame of the Quantum Decision Theory. Different types of discounting effects are analyzed and shown to enjoy a straightforward explanation within the suggested theory. We also introduce a general methodology based on self-similar approximation theory for deriving the evolution equations for the probabilities of future prospects. This provides a novel classification of possible discount factors, which include the previously known cases (exponential or hyperbolic discounting), but also predicts a novel class of discount factors that decay to a strictly positive constant for very large future time horizons. This class may be useful to deal with very long-term discounting situations associated with intergenerational public policy choices, encompassing issues such as global warming and nuclear waste disposal.
0812.2405
A New Trend in Optimization on Multi Overcomplete Dictionary toward Inpainting
cs.MM cs.AI
Recently, great attention was intended toward overcomplete dictionaries and the sparse representations they can provide. In a wide variety of signal processing problems, sparsity serves a crucial property leading to high performance. Inpainting, the process of reconstructing lost or deteriorated parts of images or videos, is an interesting application which can be handled by suitably decomposition of an image through combination of overcomplete dictionaries. This paper addresses a novel technique of such a decomposition and investigate that through inpainting of images. Simulations are presented to demonstrate the validation of our approach.
0812.2409
Sensing Models and Its Impact on Network Coverage in Wireless Sensor Network
cs.IT math.IT
Network coverage of wireless sensor network (WSN) means how well an area of interest is being monitored by the deployed network. It depends mainly on sensing model of nodes. In this paper, we present three types of sensing models viz. Boolean sensing model, shadow-fading sensing model and Elfes sensing model. We investigate the impact of sensing models on network coverage. We also investigate network coverage based on Poisson node distribution. A comparative study between regular and random node placement has also been presented in this paper. This study will be useful for coverage analysis of WSN.
0812.2411
Probabilistic SVM/GMM Classifier for Speaker-Independent Vowel Recognition in Continues Speech
cs.MM cs.AI
In this paper, we discuss the issues in automatic recognition of vowels in Persian language. The present work focuses on new statistical method of recognition of vowels as a basic unit of syllables. First we describe a vowel detection system then briefly discuss how the detected vowels can feed to recognition unit. According to pattern recognition, Support Vector Machines (SVM) as a discriminative classifier and Gaussian mixture model (GMM) as a generative model classifier are two most popular techniques. Current state-ofthe- art systems try to combine them together for achieving more power of classification and improving the performance of the recognition systems. The main idea of the study is to combine probabilistic SVM and traditional GMM pattern classification with some characteristic of speech like band-pass energy to achieve better classification rate. This idea has been analytically formulated and tested on a FarsDat based vowel recognition system. The results show inconceivable increases in recognition accuracy. The tests have been carried out by various proposed vowel recognition algorithms and the results have been compared.
0812.2454
On the statistical physics of directed polymers in a random medium and their relation to tree codes
cs.IT math.IT
Using well-known results from statistical physics, concerning the almost-sure behavior of the free energy of directed polymers in a random medium, we prove that random tree codes achieve the distortion-rate function almost surely under a certain symmetry condition.
0812.2458
Square Complex Orthogonal Designs with no Zero Entry for any $2^m$ Antennas
cs.IT math.IT
Space-time block codes from square complex orthogonal designs (SCOD) have been extensively studied and most of the existing SCODs contain large number of zeros. The zeros in the designs result in high peak-to-average power ratio and also impose a severe constraint on hardware implementation of the code while turning off some of the transmitting antennas whenever a zero is transmitted. Recently, SCODs with no zero entry have been constructed for $2^a$ transmit antennas whenever $a+1$ is a power of 2. Though there exists codes for 4 and 16 transmit antennas with no zero entry, there is no general method of construction which gives codes for any number of transmit antennas. In this paper, we construct SCODs for any power of 2 number of transmit antennas having all its entries non-zero. Simulation results show that the codes constructed in this paper outperform the existing codes for the same number of antennas under peak power constraint while performing the same under average power constraint.
0812.2535
Pattern Recognition and Memory Mapping using Mirroring Neural Networks
cs.AI cs.NE
In this paper, we present a new kind of learning implementation to recognize the patterns using the concept of Mirroring Neural Network (MNN) which can extract information from distinct sensory input patterns and perform pattern recognition tasks. It is also capable of being used as an advanced associative memory wherein image data is associated with voice inputs in an unsupervised manner. Since the architecture is hierarchical and modular it has the potential of being used to devise learning engines of ever increasing complexity.
0812.2559
A Separation Algorithm for Improved LP-Decoding of Linear Block Codes
cs.IT math.IT
Maximum Likelihood (ML) decoding is the optimal decoding algorithm for arbitrary linear block codes and can be written as an Integer Programming (IP) problem. Feldman et al. relaxed this IP problem and presented Linear Programming (LP) based decoding algorithm for linear block codes. In this paper, we propose a new IP formulation of the ML decoding problem and solve the IP with generic methods. The formulation uses indicator variables to detect violated parity checks. We derive Gomory cuts from our formulation and use them in a separation algorithm to find ML codewords. We further propose an efficient method of finding cuts induced by redundant parity checks (RPC). Under certain circumstances we can guarantee that these RPC cuts are valid and cut off the fractional optimal solutions of LP decoding. We demonstrate on two LDPC codes and one BCH code that our separation algorithm performs significantly better than LP decoding.
0812.2574
Feature Selection By KDDA For SVM-Based MultiView Face Recognition
cs.CV cs.LG
Applications such as face recognition that deal with high-dimensional data need a mapping technique that introduces representation of low-dimensional features with enhanced discriminatory power and a proper classifier, able to classify those complex features. Most of traditional Linear Discriminant Analysis suffer from the disadvantage that their optimality criteria are not directly related to the classification ability of the obtained feature representation. Moreover, their classification accuracy is affected by the "small sample size" problem which is often encountered in FR tasks. In this short paper, we combine nonlinear kernel based mapping of data called KDDA with Support Vector machine classifier to deal with both of the shortcomings in an efficient and cost effective manner. The proposed here method is compared, in terms of classification accuracy, to other commonly used FR methods on UMIST face database. Results indicate that the performance of the proposed method is overall superior to those of traditional FR approaches, such as the Eigenfaces, Fisherfaces, and D-LDA methods and traditional linear classifiers.
0812.2575
Face Detection Using Adaboosted SVM-Based Component Classifier
cs.CV cs.LG
Recently, Adaboost has been widely used to improve the accuracy of any given learning algorithm. In this paper we focus on designing an algorithm to employ combination of Adaboost with Support Vector Machine as weak component classifiers to be used in Face Detection Task. To obtain a set of effective SVM-weaklearner Classifier, this algorithm adaptively adjusts the kernel parameter in SVM instead of using a fixed one. Proposed combination outperforms in generalization in comparison with SVM on imbalanced classification problem. The proposed here method is compared, in terms of classification accuracy, to other commonly used Adaboost methods, such as Decision Trees and Neural Networks, on CMU+MIT face database. Results indicate that the performance of the proposed method is overall superior to previous Adaboost approaches.
0812.2602
The statistical restricted isometry property and the Wigner semicircle distribution of incoherent dictionaries
cs.IT cs.DM math.IT math.PR
In this article we present a statistical version of the Candes-Tao restricted isometry property (SRIP for short) which holds in general for any incoherent dictionary which is a disjoint union of orthonormal bases. In addition, we show that, under appropriate normalization, the eigenvalues of the associated Gram matrix fluctuate around 1 according to the Wigner semicircle distribution. The result is then applied to various dictionaries that arise naturally in the setting of finite harmonic analysis, giving, in particular, a better understanding on a remark of Applebaum-Howard-Searle-Calderbank concerning RIP for the Heisenberg dictionary of chirp like functions.
0812.2702
Standard Logics Are Valuation-Nonmonotonic
cs.LO cs.AI quant-ph
It has recently been discovered that both quantum and classical propositional logics can be modelled by classes of non-orthomodular and thus non-distributive lattices that properly contain standard orthomodular and Boolean classes, respectively. In this paper we prove that these logics are complete even for those classes of the former lattices from which the standard orthomodular lattices and Boolean algebras are excluded. We also show that neither quantum nor classical computers can be founded on the latter models. It follows that logics are "valuation-nonmonotonic" in the sense that their possible models (corresponding to their possible hardware implementations) and the valuations for them drastically change when we add new conditions to their defining conditions. These valuations can even be completely separated by putting them into disjoint lattice classes by a technique presented in the paper.
0812.2709
Variations on a theme by Schalkwijk and Kailath
cs.IT math.IT
Schalkwijk and Kailath (1966) developed a class of block codes for Gaussian channels with ideal feedback for which the probability of decoding error decreases as a second-order exponent in block length for rates below capacity. This well-known but surprising result is explained and simply derived here in terms of a result by Elias (1956) concerning the minimum mean-square distortion achievable in transmitting a single Gaussian random variable over multiple uses of the same Gaussian channel. A simple modification of the Schalkwijk-Kailath scheme is then shown to have an error probability that decreases with an exponential order which is linearly increasing with block length. In the infinite bandwidth limit, this scheme produces zero error probability using bounded expected energy at all rates below capacity. A lower bound on error probability for the finite bandwidth case is then derived in which the error probability decreases with an exponential order which is linearly increasing in block length at the same rate as the upper bound.
0812.2719
Secret Sharing over Fast-Fading MIMO Wiretap Channels
cs.IT math.IT
Secret sharing over the fast-fading MIMO wiretap channel is considered. A source and a destination try to share secret information over a fast-fading MIMO channel in the presence of a wiretapper who also makes channel observations that are different from but correlated to those made by the destination. An interactive authenticated unrestricted public channel is also available for use by the source and destination in the secret sharing process. This falls under the "channel-type model with wiretapper" considered by Ahlswede and Csiszar. A minor extension of their result (to continuous channel alphabets) is employed to evaluate the key capacity of the fast-fading MIMO wiretap channel. The effects of spatial dimensionality provided by the use of multiple antennas at the source, destination, and wiretapper are then investigated.