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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Arvind Ganesh Zihan Zhou Yi Ma Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign USA

In this paper, we show how two classical sparse recovery algorithms, orthogonal matching pursuit and basis pursuit, can be naturally extended to recover block-sparse solutions for subspace-sparse signals. A subspace-sparse signal is sparse with respect to a set of subspaces, instead of atoms. By generalizing the notion of mutual incoherence to the set of subspaces, we show that all classical sufficient conditions remain exactly the same for these algorithms to work for subspace-sparse signals, in both noiseless and noisy cases. The sufficient conditions provided are easy to verify for large systems. We conduct simulations to compare the performance of the proposed algorithms.

关键词： Matching pursuit algorithms Sufficient conditions Sparks pursuit algorithms Vectors Dictionaries Linear systems Sparse matrices Signal representations Optimization methods

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Block-sparsity: Coherence and efficient recovery

Block-sparsity: Coherence and efficient recovery

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yonina C. Eldar Helmut Bolcskei Technion-Israel Institute of Technology Haifa Israel ETH Zurich Zurich Switzerland

We consider compressed sensing of block-sparse signals, i.e., sparse signals that have nonzero coefficients occurring in clusters. Based on an uncertainty relation for block-sparse signals, we define a block-coherence measure and 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 lscr 2 /lscr 1 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.

关键词： Matching pursuit algorithms Compressed sensing Clustering algorithms pursuit algorithms Robustness Sufficient conditions Uncertainty Coherence Wireless communication Context

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Gait Recognition Using Wavelet Packet Silhouette Representation and Transductive Support Vector Machines

Gait Recognition Using Wavelet Packet Silhouette Representat...

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Congress on Image and Signal Processing, CISP

作者： Farzin Dadashi Babak N. Araabi Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Hospital Detroit MI USA

Gait is an idiosyncratic biometric that can be used for human identification at a distance and as a result gained growing interest in intelligent visual surveillance. In this paper, an efficient gait recognition method based on describing subject outer body contour deformations using wavelet packets is proposed. With the use of matching pursuit algorithm, k bases of wavelet packet tree that have maximum similarity to the signal are selected and corresponding coefficients are used as features. Finally, transductive support vector machine (TSVM) classification is utilized on computed eigengait space for semi-supervised identification. The proposed method of selecting features which uses a complete orthogonal or near orthogonal basis from a wavelet packet library of bases and investigating the correlational structure of gait features for each individual using TSVM, result in encouraging identification performance.

关键词： Wavelet packets Support vector machines Matching pursuit algorithms Biometrics Humans Machine intelligence Surveillance pursuit algorithms Support vector machine classification Libraries

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A Practical Sparse Channel Estimation for Current OFDM Standards

A Practical Sparse Channel Estimation for Current OFDM Stand...

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International Conference on Telecommunications (ICT)

作者： Mahdi Soltanolkotabi Mojtaba Soltanalian Arash Amini Farokh Marvasti Department of Electrical Engineering Sharif University of Technology Tehran Iran

Wireless channels especially for OFDM transmissions can be precisely approximated by a time varying filter with sparse taps (in the time domain). Sparsity of the channel is a criterion which can highly improve the channel estimation task in mobile applications. In sparse signal processing, many efficient algorithms have been developed for finding the sparsest solution to linear equations (Basis pursuit, Matching pursuit) in the presence of noise. In current OFDM standards, a number of the ending subcarriers at both positive and negative frequencies are left unoccupied (for ease of analog filtering at the receiver) which results in an ill-conditioned frequency to time transformation matrix. This means that the initial estimate for the impulse response of the channel (in time) easily varies as the noise vector changes. Thus in this case we cannot use most of the proposed algorithms in sparse signal processing. In this paper, we propose iteration with adaptive thresholding and MMSE methods to overcome this difficulty. Simulation results indicate that the proposed method is almost perfect for stationary channels and only minor performance degradation is observed with increase of Doppler frequency.

关键词： Channel estimation OFDM Signal processing algorithms Matching pursuit algorithms Filters pursuit algorithms Equations Filtering Sparse matrices Adaptive signal processing

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A Novel Matching pursuit Algorithm with Adaptive Subdictionary

A Novel Matching Pursuit Algorithm with Adaptive Subdictiona...

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9th International Conference on Signal Processing

作者： Guo Jinku Liu Guangbin Yang Xiaojun Xian Res Inst Hitech Dept Automat Xian 710025 Peoples R China Tsinghua Univ Dept Automat Beijing 100084 Peoples R China

ISBN: (纸本)9781424421787

Sparse decomposition of a signal can be obtained by decomposing the signal in an overcomplete dictionary. Matching pursuit (MP) is a greedy algorithm to realize such decompositions, and has been widely studied in many signal processing researches. Through exploiting the structure shared by these so-called adaptive decomposition dictionaries, we propose a novel MP algorithm which can reduce computation and storage requirement dramatically.

关键词： Matching pursuit algorithms pursuit algorithms Dictionaries Signal processing algorithms Time frequency analysis Automation Signal resolution Cities and towns Greedy algorithms Adaptive signal processing

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Computational geometry in navigation and path planning

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IEEE ROBOTICS & AUTOMATION MAGAZINE 2008年第2期15卷 6-7页

作者： Gavrilova, Marina Cortes, Jorge Jarvis, Raymond Department of Physics National Taiwan Normal University Taipei Taiwan R.O.C.

The six contributions to this special issue focus on computational geometry in navigation and path planning. The issue presents the applications of computational geometry in obstacle avoidance, path planning with minimum clearance, autonomous mobile robot navigation, exploration of unknown polygonal environments, and it explores the practical relevance to the geographical information systems, mobile networks, risk avoidance, security, games, and online system design.

关键词： Computational geometry Navigation Path planning Mobile robots Orbital robotics pursuit algorithms Robot sensing systems Intelligent robots Intelligent sensors Robotics and automation

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L1 regularized projection pursuit for additive model learning

L1 regularized projection pursuit for additive model learnin...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Xiao Zhang Lin Liang Xiaoou Tang Heung-Yeung Shum Center for Advanced Study Tsinghua University Beijing China Microsoft Research Asia Beijing China Microsoft Corporation Redmond Washington D.C. DC USA

In this paper, we present a L 1 regularized projection pursuit algorithm for additive model learning. Two new algorithms are developed for regression and classification respectively: sparse projection pursuit regression and sparse Jensen-Shannon Boosting. The introduced L 1 regularized projection pursuit encourages sparse solutions, thus our new algorithms are robust to overfitting and present better generalization ability especially in settings with many irrelevant input features and noisy data. To make the optimization with L 1 regularization more efficient, we develop an ldquoinformative feature firstrdquo sequential optimization algorithm. Extensive experiments demonstrate the effectiveness of our proposed approach.

关键词： pursuit algorithms Boosting Robustness Unsolicited electronic mail Additives Asia Neural networks Laplace equations Cost function

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Tree structured pursuit for simultaneous image approximation

Tree structured pursuit for simultaneous image approximation

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Ariel J. Bernal Sebastian E. Ferrando Department of Electrical Engineering Ryerson University Toronto ONT Canada Department of Mathematics Ryerson University Toronto ONT Canada

The paper introduces an adapted orthonormal system to approximate a collection of given images. The associated construction is performed by a pursuit algorithm constrained to build a tree; the pursuit maximization is performed over a large dictionary of Haar wavelet-like functions. The approximations are given by vector valued discrete martingales that converge to the vector of input images. A natural application for our construction is the case when the set of images is given by a sequence of video frames. We describe the trade off between the size of the input set and the quality of the approximation and provide examples and comparisons.

关键词： Image coding Partitioning algorithms Image storage Costs pursuit algorithms Video compression Random variables Dictionaries Image converters Approximation algorithms

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A pursuit game with range-only measurements

A pursuit game with range-only measurements

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IEEE Conference on Decision and Control

作者： Shaunak D. Bopardikar Francesco Bullo Joao P. Hespanha Center for Control Dynamical Systems and Computation(CCDC) University of California슠Santa Barbara Santa Barbara CA USA

We address a discrete-time, pursuit-evasion game with alternate moves played between two kinds of players: the pursuer and the evader. The pursuer wishes to capture the evader while the evader¿s goal is to avoid capture. By capture, we mean that the distance between the players is no greater than 1 unit. We assume simple, first-order motion kinematics for the players. The pursuer can move with a step size of at most 1 unit while the evader can move with a maximum step size of ß ¿ 1 units. The pursuer is able to measure only its distance from the evader, before and after the evader¿s move. We propose a capture strategy and first show that for the game played in ¿ 2 , if ß ¿ 0.5, then a single pursuer captures the evader in finite time. Next, we show that if the game is played in ¿ 3 and if ß ¿ 0.5, then with a modified strategy, two identical cooperative pursuers capture the evader in finite time. Finally, we shed light on the performance of the capture strategy in the case of ß ¿ [0.5, 1] and the case of sensing errors via simulations. We also present a simulation study of a version of this game with simultaneous moves.

关键词： Target tracking Kinematics Surveillance Surges pursuit algorithms Sufficient conditions Algorithm design and analysis Biological materials Collaborative work Biotechnology

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Intrusion Detection System Based on Matching pursuit

Intrusion Detection System Based on Matching Pursuit

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International Workshop on Intelligent Networks and Intelligent Systems (ICINIS)

作者： Rafal Renk Lukasz Saganowski Witold Holubowicz Michal Choras Adam Mickiewicz University Poznań Poland

In this paper we present our original methodology, in which Matching pursuit is used for networks anomaly and intrusion detection. We propose to use mean projection of the reconstructed network signal to determine if ... 详细信息

关键词： Intrusion detection Matching pursuit algorithms Signal processing algorithms Dictionaries Discrete wavelet transforms Continuous wavelet transforms Wavelet analysis Intelligent networks pursuit algorithms Telecommunication traffic

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