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检索条件"主题词=Pursuit algorithms"

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Performance Study of Various Sparse Representation Methods Using Redundant Frames

Performance Study of Various Sparse Representation Methods U...

引用

Annual Conference on Information Sciences and Systems (CISS)

作者： Mehmet Akcakaya Vahid Tarokh School of Engineering and Applied Sciences Harvard University Cambridge MA USA

Sparse representations have recently received wide attention because of their numerous potential applications. In this paper, we consider sparse representations of signals with at most L non-zero coefficients using a frame F of size M in C N . We bound the average distortion of such a representation for any arbitrary frame F by a numerical lower bound that is only a function of the sparsity epsiv = L/N of the representation, and the redundancy (r-1) = M/N-1 of F. This numerical lower bound is shown to be much stronger than the analytical and asymptotic bounds of in low dimensions (e.g. N = 6,8, 10), but it is much less straightforward to compute. We then study the performance of randomly generated frames with respect to this numerical lower bound, and to the analytical and asymptotic bounds. When the optimal sparse representation algorithm is used, it is observed that randomly generated frames perform about 2 dB away from the theoretical lower bound in low dimensions. We use the greedy orthogonal matching pursuit (OMP) algorithm to study the performance of randomly generated frames in higher dimensions. For small values of epsiv, randomly generated frames using OMP perform close to the lower bound and the results suggest that the loss of the sub-optimal search using orthogonal matching pursuit algorithm grows as a function of epsiv. As N grows, a concentration phenomenon for the performance of randomly generated frames about their average is observed in all cases, even when using the OMP algorithm.

关键词： Matching pursuit algorithms pursuit algorithms Vectors Decoding Signal analysis Performance analysis Dictionaries Sparse matrices Distortion measurement

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Applications of Basis Selection algorithms in Communication Problems

Applications of Basis Selection Algorithms in Communication ...

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IEEE Signal Processing and Communications Applications (SIU)

作者： Karabulut Kurt Yongacoglu School of Information Technology and Engineering University of Ottawa ONT Canada

In this paper, we study the application of sequential basis selection (SBS) algorithms in two different communication problems. These problems represent different cases in terms of the structure of their set of equations. The two considered cases are; undercomplete set of equations (sparse channel estimation problem) and overcomplete set of equations. These cases are carefully selected in order to demonstrate that SBS algorithms can be applied to both types of equations. The basic matching pursuit (BMP) and the orthogonal matching pursuit (OMP) algorithms are selected as the SBS algorithms. In sparse channel estimation problem, the BMP and the OMP algorithms are compared with the least square channel estimates and the minimum variance unbiased estimates (MVUE). It is shown that the OMP algorithm gives estimates that are almost converging to MVUE. In angle of arrival (AOA) detection problem, the detection performances of the BMP and OMP algorithms are compared with the well known MUSIC algorithm and the Cramer Rao bounds. It is shown that their performances exceed that of MUSIC for correlated signals

关键词： Matching pursuit algorithms Equations Sociotechnical systems Channel estimation pursuit algorithms Multiple signal classification Information technology Least squares approximation Cramer-Rao bounds

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Sinusoidal modeling of audio and speech using psychoacoustic-adaptive matching pursuits

Sinusoidal modeling of audio and speech using psychoacoustic...

引用

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

作者： R. Heusdens R. Vafin W.B. Kleijn Dept. of Mediamatics Delft University of Technology Delft The Netherlands Dept. of Speech Music and Hearing KTH Royal Institute of Technology Stockholm Sweden

We propose a segment-based matching pursuit algorithm where the psychoacoustical properties of the human auditory system are taken into account. Rather than scaling the dictionary elements according to auditory perception, we define a psychoacoustic-adaptive norm on the signal space which can be used for assigning the dictionary elements to the individual segments in a rate-distortion optimal manner. The new algorithm is asymptotically equal to signal-to-mask ratio based algorithms in the limit of infinite analysis window length. However, the new algorithm provides a significantly improved selection of the dictionary elements for finite window length.

关键词： Speech Dictionaries Matching pursuit algorithms Psychology Psychoacoustic models pursuit algorithms Humans Auditory system Rate-distortion Signal analysis

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Multi-antenna OFDM channel feedback compression exploiting sparsity

Multi-antenna OFDM channel feedback compression exploiting s...

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European Wireless 2013;19th European Wireless Conference

作者： Thorsten Wild Cornelis Hoek Guenther Herzog Johannes Koppenborg The authors are with Bell Laboratories

In order to enable advanced downlink multiantenna techniques, like MU-MIMO or Network MIMO, accurate channel knowledge at the transmitter is required. In order to save scarce uplink resources, the feedback has to be compressed. This paper provides a practical channel feedback compression technique which exploits the sparse nature of radio channels and removes redundant and irrelevant information. It introduces a novel path detection algorithm by modifying the existing orthogonal matching pursuit algorithm. Furthermore it presents efficient practical bit loading techniques. Channel aging effects can be efficiently handled by prediction, as shown in this paper. The prediction integrates very well into the presented feedback compression framework. For application to existing radio propagation channel compression, measurement results are discussed, dealing with the question how sparse the actual channel is.

关键词： multiple antenna Feedback wireless channels ageing effects Redundant Transmitters Orthogonal frequency division multiplexing pursuit algorithms Matching pursuit algorithms compression order

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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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Reduced complexity bounded error subset selection

Reduced complexity bounded error subset selection

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

作者： M. Alghoniemy A.H. Tewfik Department of Electrical Engineering Alexandria University Alexandria Egypt Department of Electrical and Computer Engineering University of Minnesota Minneapolis MN USA

A reduced complexity version of the bounded error subset selection (BESS) algorithm is proposed. By relaxing the integer constraint in the original BESS algorithm, we show that the BESS problem can be reformulated as an ordinary linear program instead of an integer program with exponential worst-case complexity. We retain the sparseness of the representation in the modified BESS by weighting the dictionary with the minimum 2-norm solution of the subset selection problem corresponding to the BESS problem at hand. The proposed algorithm is compared to the basis pursuit, orthogonal matching pursuit, and the best orthogonal basis algorithms. It is shown that the proposed algorithm has a better packing property and an improved rate-distortion behavior.

关键词： Matching pursuit algorithms Signal processing algorithms Dictionaries Vectors Signal representations Computer errors pursuit algorithms Iterative algorithms Greedy algorithms Approximation algorithms

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Simulator of multi-AGV robotic industrial environments

Simulator of multi-AGV robotic industrial environments

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IEEE International Conference on Industrial Technology (ICIT)

作者： K. Petrinec Z. Kovacic A. Marozin Faculty of EE&C University of Zagreb Zagreb CROATIA Euroimpianti srl Via Lago di Vico Vicenza ITALY

This paper is concerned with simulation of floor shop layouts that may contain a number of robotic manufacturing cells and a number of automated guided vehicles (AGVs) that commutate between dynamically determined starting and end nodes. We describe improvements of the AGVs pure pursuit path planning algorithm that were achieved by using a simulator for the off-line and on-line testing purposes. Simulator enables more efficient planning of the whole manufacturing process, optimization of the number of AGVs for a given floor shop, and easy modifications before implementation of the real system.

关键词： Service robots Robotics and automation Manufacturing industries Manufacturing automation Pulp manufacturing Virtual manufacturing Vehicles Path planning pursuit algorithms Testing

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Adaptive filtering algorithms for promoting sparsity

Adaptive filtering algorithms for promoting sparsity

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

作者： B.D. Rao Bongyong Song Department of Electrical and Computer Engineering La Jolla CA USA

We provide a mathematical framework for developing adaptive filtering algorithms for exploiting/enforcing sparsity. The approach is based on minimizing a regularized mean squared error criterion with sparsity being promoted by the regularizing term which consists of a diversity measure. A steepest descent algorithm (SDA) is developed to minimize the regularized cost function. Then we extend the algorithm to the adaptive environment and develop a class of algorithms, which we term the pLMS algorithm class and which incudes important variants - pLLMS (leaky pLMS) and pNLMS (normalized pLMS). The framework is quite general and encompasses a broad range of adaptive algorithms with the pNLMS having similarity with the proportionate normalized least-mean-squares (PNLMS) algorithm. Computer simulations have been conducted using the echo canceller application as an example of a sparse environment. The simulations clearly show the ability of the developed algorithms to exploit the inherent sparsity structure, thereby outperforming conventional algorithms like the NLMS algorithm in this application.

关键词： Adaptive filters Filtering algorithms Matching pursuit algorithms Least squares approximation Cost function Echo cancellers Adaptive algorithm Algorithm design and analysis pursuit algorithms Vectors

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Tap Selection Based Multipath Channel Equalization For UWB Systems

Tap Selection Based Multipath Channel Equalization For UWB S...

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

作者： Zhiwei Lin A.B. Premkumar A.S. Madhukumar Institute for Infocomm Research Singapore School of Computer Engineering Nanyang Technological University Singapore

In this paper, tap selection based Minimum Mean Square Error (MMSE) equalization technique is discussed for ultra wideband (UWB) systems in the presence of inter symbol interference (ISI) and multiple access interference (MAI). A novel tap selection technique based on matching pursuit (MP) algorithm is proposed. Given finite training sample support, diagonal loading (DL) technique is incorporated into MP algorithm to insure the robustness of tap selection. Moreover, a fast heuristic MP based tap selection technique is developed to facilitate the tradeoff between equalization performance and computational complexity. Simulation results show that the proposed tap selection based equalizer outperforms the RAKE receiver and the conventional MMSE equalizer significantly given the same amount of training symbols

关键词： Multipath channels Matching pursuit algorithms Multiple access interference Equalizers Mean square error methods Ultra wideband technology Intersymbol interference pursuit algorithms Robustness Computational complexity

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Sparse channel estimation with regularization method using convolution inequality for entropy

Sparse channel estimation with regularization method using c...

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International Joint Conference on Neural Networks (IJCNN)

作者： Dongho Han Sung-Phil Kim J.C. Principe Computational NeuroEngineering Lab Department of Electrical and Computer Engineering University of Florida Gainesville FL USA

In this paper, we show that the sparse channel estimation problem can be formulated as a regularization problem between mean squared error (MSE) and the L 1 -norm constraint of the channel impulse response. A simple adaptive method to solve regularization problem using the convolution inequality for entropy is proposed. Performance of this proposed regularization method is compared to the Wiener filter, the matching pursuit (IMP) algorithm and the information criterion based method. The results show that the estimate of the sparse channel using the MSE criterion with the L 1 -norm constraint outperforms the Wiener filter and the conventional sparse solution methods in terms of MSE of the estimates and the generalization performance.

关键词： Channel estimation Convolution Entropy Matching pursuit algorithms pursuit algorithms Wiener filter Delay estimation Vectors Neural engineering Computer errors

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