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检索条件"主题词=Pursuit algorithms"

共 488 条记录，以下是121-130 订阅

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GRADIENT POLYTOPE FACES pursuit FOR LARGE SCALE SPARSE RECOVERY PROBLEMS

GRADIENT POLYTOPE FACES PURSUIT FOR LARGE SCALE SPARSE RECOV...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Aris Gretsistas Ivan Damnjanovic Mark D. Plumbley Queen Mary University of London Centre for Digital Music Mile End Road E1 4NS London UK

ISBN: (纸本)9781424442959

Polytope Faces pursuit is a greedy algorithm that performs Basis pursuit with similar order complexity to Orthogonal Matching pursuit. The algorithm adds one basis vector at a time and adopts a path-following approach based on the geometry of the polar polytope associated with the dual Linear Program. Its initial implementation uses the method of Cholesky factorization to update the solution vector at each step, which can be computationally expensive for solving large scale problems as it requires the succesive storage of large matrices. In this paper, we present a different approach using directional updates to estimate the solution vector at each time. The proposed method uses the gradient descent method, reducing the memory requirements and computational complexity. We demonstrate the application of this Gradient Polytope Faces pursuit algorithm to a source separation problem.

关键词： Sparse representation greedy algorithm Polytope Faces pursuit Gradient descent Source Separation Source separation greedy algorithm sparse representation Polytopes pursuit algorithms memory requirements Scale formation Cholesky factorisation descent method LARGE gene

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Sparse channel estimation using orthogonal matching pursuit algorithm

Sparse channel estimation using orthogonal matching pursuit ...

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IEEE Conference on Vehicular Technology (VTC)

作者： G.Z. Karabulut A. Yongacoglu School of Information Technology and Engineering University of Ottawa ONT Canada

Sparse channels are encountered in several communication applications. Exploiting the sparsity, a channel estimate can be obtained by using a matching pursuit (MP) algorithm. Previously, it was demonstrated that the MP based channel estimation outperforms the conventional least squares (LS) estimation algorithm for sparse channels. In this paper, we propose to use the orthogonal matching pursuit (OMP) algorithm for channel estimation. Using OMP, the convergence problem in MP algorithm based on re-selection of the basis vectors is eliminated. It is also verified that by avoiding the re-selection problem more accurate channel estimates can he obtained by using the OMP algorithm. The performance of decision feedback equalizers based on the channel estimates obtained by using the MP and OMP algorithms are compared, verifying that the OMP outperforms the MP, with a comparable computational complexity.

关键词： Matching pursuit algorithms Channel estimation pursuit algorithms Signal processing algorithms Decision feedback equalizers Signal resolution Fourier transforms Least squares approximation Discrete wavelet transforms Discrete cosine transforms

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Application of Adaptive Kernel Matching pursuit to Estimate Mixture Pixel Proportion

Application of Adaptive Kernel Matching Pursuit to Estimate ...

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International Conference on Image and Graphics (ICIG)

作者： Wu Bo Wang XiaoQin Huang Bo Spatial information research Center of Fujian Province Fuzhou university Fuzhou China Department of geography and resource management The Chinese University of Hong-Kong New Territories Hong Kong China

An adaptive kernel matching pursuit (AKMP) algorithm to estimate mixture pixel proportion of remotely sensed image has been proposed. The AKMP algorithm applies greedy sparse approximation algorithm to the feature space induced by a nonlinear kernel function, and can therefore be able to capture nonlinear effects of image and performed better than conventional linear approaches. Moreover, it has the capability of adaptive selection of the kernel parameter before starting the greedy approximating procedure to avoid complex procedures of kernel function parameter selection. Experiments with ETM+ associated with IKONOS image have been carried out, and the result demonstrates that the proposed method can provide accurate proportion estimation. Comparisons with support vector regression (SVR) and linear mixture model (LMM) have also been done, and the experiments show that the proposed method outperform SVR and LMM in terms of RMSE.

关键词： Kernel Matching pursuit algorithms Pixel Approximation algorithms Linear regression pursuit algorithms Vectors Graphics Geography Resource management

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The adaptive matching pursuit algorithm for estimation and equalization of sparse time-varying channels

The adaptive matching pursuit algorithm for estimation and e...

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Asilomar Conference on Signals, Systems & Computers

作者： S.F. Cotter B.D. Rao Electrical and Computer Engineering Department University of California San Diego La Jolla CA USA University of California San Diego La Jolla CA US

ISBN: (纸本)0780365143

This paper addresses issues related to the estimation and equalization of channels with a large delay spread and an impulse response with significant values only over small regions. For a time-varying environment, an adaptive matching pursuit (AMP) algorithm is considered which updates the channel estimate while exploiting the channel's sparsity. From the channel estimate, the equalizer taps are then derived. We show through simulations that using AMP to track the time-varying channel gives significant improvement in equalization performance over using the LMS or RLS algorithms. We also demonstrate how ANP may be modified to more quickly adapt to a fast time-varying channel.

关键词： Matching pursuit algorithms pursuit algorithms Adaptive equalizers Time-varying channels Least squares approximation Delay estimation Resonance light scattering Intersymbol interference HDTV Underwater acoustics

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Adapting Matching pursuit Dictionaries to Waveform Structure using Particle Filtering

Adapting Matching Pursuit Dictionaries to Waveform Structure...

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Sensor Array and Multichannel Signal Processing Workshop

作者： I. Kyriakides A. Papandreou-Suppappola D. Morrell Department of Electrical Engineering Arizona State University Tempe AZ USA Department of Engineering Arizona State University Mesa AZ USA

Although the matching pursuit algorithm can accurately decompose waveforms, its use in real applications is limited. This is because it can be computationally intensive as it is based on selecting elements from complete dictionaries spanning the time-frequency plane of interest. There is, therefore, a need for smaller dictionaries that can still result in accurate waveform decompositions. In this paper, we propose the particle filter matching pursuit algorithm that adapts the dictionary to the waveform structure. This algorithm uses particle filtering, a sequential Monte Carlo approach, to estimate the dictionary suitable for the decomposition of a given waveform, and then uses the matching pursuit algorithm to decompose the waveform. We demonstrate, using simulations, that the particle filtering matching pursuit can decompose waveforms faster than the matching pursuit

关键词： Matching pursuit algorithms Dictionaries Matched filters pursuit algorithms Filtering algorithms Time frequency analysis Data mining Atomic measurements Electronic mail Particle filters

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Quantized high resolution pursuit

Quantized high resolution pursuit

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IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis

作者： R. Montufar-Chaveznava F. Garcia-Ugalde Inst. de Fisiologia Celular Univ. Nacional Autonoma de Mexico Mexico City Mexico

Because of their properties, adaptive decomposition techniques have been hardly studied in order to apply them to different works, such as signal characterization, compact representation, feature extraction, noise subtraction, etc. High resolution pursuit is one of the techniques developed which principally provides a very good super-resolution without requiring expensive computation, compared with other super-resolution techniques such as basis pursuit. When an adaptive decomposition technique is employed for compact representation, it is necessary to consider the introduction of a quantization stage for better results. V. Goyal (see SPIE vol.3024, p.2-12) presented good result and has also studied quantization in adaptive decomposition techniques, specifically with the matching pursuit. We test quantization with the high resolution pursuit technique in order to analyze some of the results obtained.

关键词： Matching pursuit algorithms Signal resolution Dictionaries pursuit algorithms Quantization Vectors Feature extraction Atomic measurements Circuit noise Testing

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Controlling Nonlinear Dynamic Systems with Projection pursuit Learning

Controlling Nonlinear Dynamic Systems with Projection Pursui...

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International IEEE Conference on Intelligent Systems, IS

作者： Clodoaldo A. M. Lima Pablo A. D. Castro Andre L. V. Coelho Cynthia Junqueira Fernando J. Von Zuben Laboratory of Bioinformatics and Bio-inspired Computing (LBiC) State University of Campinas-UNICAMP Sao Paulo Brazil Applied Informatics (MIA) University of Fortaleza-UNIFOR Fortaleza Ceara Brazil Laboratory of Signal Processing for Communications (DSPCom) State University of Campinas-UNICAMP Sao Paulo Brazil

Projection pursuit learning (PPL) refers to a well-known constructive learning algorithm characterized by a very efficient and accurate computational procedure oriented to nonparametric regression. It has been employed as a means to counteract some problems related to the design of artificial neural network (ANN) models, namely, the estimation of a (usually large) number of free parameters, the proper definition of the model's dimension, and the choice of the sources of nonlinearities (activation functions). In this work, the potentials of PPL are exploited through a different perspective, namely, in designing one-hidden-layer feedforward ANNs for the adaptive control of nonlinear dynamic systems. For such purpose, the proposed methodology is divided into three stages. In the first, the model identification process is undertaken. In the second, the ANN structure is defined according to an offline control setting. In these two stages, the PPL algorithm estimates not only the optimal number of hidden neurons but also the best activation function for each node. The final stage is performed online and promotes a fine-tuning in the parameters of the identification model and the controller. Simulation results indicate that it is possible to design effective neural models based on PPL for the control of nonlinear multivariate systems, with superior performance when compared to benchmarks

关键词： Nonlinear control systems Control systems Artificial neural networks Aerodynamics Neurons pursuit algorithms Adaptive control Nonlinear dynamical systems Laboratories System identification

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Identification of distillation column operating conditions with orthogonal matching pursuit

Identification of distillation column operating conditions w...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： F. Neves A. Shmilovici J. Aguilar-Martin LEA SICA (LAAS-CNRS) Toulouse France

A distillation column has a complex nonlinear separation process with time delays. Using the orthogonal matching pursuit algorithm, a fuzzy model is identified for the distillation column started from an empty operati... 详细信息

关键词： Distillation equipment Matching pursuit algorithms Fuzzy systems pursuit algorithms Fuzzy sets Buildings Function approximation Inference algorithms Separation processes Delay effects

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Video coding using a deformation compensation algorithm based on adaptive matching pursuit image decompositions

Video coding using a deformation compensation algorithm base...

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IEEE International Conference on Image Processing

作者： O. Divorra Escoda P. Vandergheynst Signal Processing Institute (ITS) Swiss Federal Institute of Technology Lausanne Switzerland

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Mallat's Matching pursuit of sperm whale clicks in real-time using Daubechies 15 wavelets

Mallat's Matching Pursuit of sperm whale clicks in real-time...

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New Trends for Environmental Monitoring Using Passive Systems

作者： Fabien Lelandais Herve Glotin CNRS UMR6168 Systems and Information Sciences Laboratory (LSIS) Universite du Sud Toulon La Garde France

This article presents how the wavelet matching pursuit (MP) algorithm can perform in real-time, ocean noise elimination and whale clicks detection and segregation. This work is based on two recent advances: the first [Adam 05]proposes to analyze sperm whale signals with Daubechies 15 wavelets. The second is the fast implementation of the MP by INRIA Rennes team [MPTK 06]. We first show that one can interface DB15 with this toolkit. Second, we demonstrate, for the first time, a real use of DB15 on two long whale records reference datasets containing one or several sperm whales to address the click labeling issue. Experiments are conducted on AUTEC Bahamas data, whales are from 5 to 10 km far from the bottom mounted hydrophone. We show that DB15 are efficient for real time click detection, ocean noise and echoes removal. We get 85% of click detection for less than 20% of false alarm. We finally apply our approach to 3 co-clicking whales, and we show promising results of automatic fast segregation and click labeling of simultaneous emitting whales.

关键词： Matching pursuit algorithms Whales Acoustic noise Oceans Labeling Acoustic waves pursuit algorithms Wavelet analysis Acoustic emission Real time systems

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