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检索条件"主题词=Pursuit algorithms"

共 488 条记录，以下是181-190 订阅

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Sparse component analysis of overcomplete mixtures by improved basis pursuit method

Sparse component analysis of overcomplete mixtures by improv...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： P. Georgiev A. Cichoki Laboratory for Advanced Brain Signal Processing Brain Science Institute RIKEN Wako Saitama Japan RIKEN Lab. for Advanced Brain Signal Processing Saitama Japan Rikagaku Kenkyujo Wako Saitama JP Brain Sci. Inst. RIKEN Wako Japan

We formulate conditions under which we can solve precisely the blind source problem (BSS) in the under-determined case (less sensors than sources), up to permutation and scaling of sources. Under these conditions, which include information about sparseness of the sources (and hence we call the problem sparse component analysis (SCA, we can: 1) identify the mixing matrix uniquely (up to scaling and permutation); and 2) recover uniquely the original sources. We present a new algorithm for estimation of the mixing matrix, as well as an algorithm for SCA (estimation of sparse sources), which improves the standard basis pursuit method of S. Chen, D. Donoho, and M. Sounders (see inbid., no 1, p33-61, 1998) - when the mixing matrix is known or correctly estimated. Our methods are examples.

关键词： Sparse matrices Source separation Independent component analysis pursuit algorithms Blind source separation Signal processing algorithms Signal processing Information analysis Dictionaries Image analysis

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On-line identification of nonlinear systems using adaptive matching pursuit

On-line identification of nonlinear systems using adaptive m...

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IEEE Convention of the Electrical and ELectronic Engineers in Israel

作者： A. Shmilovici O. Maimon Department of Manufacturing Engineering Boston University Boston MA USA Department of Industrial Engineering Tel-Aviv University Tel-Aviv Israel

A reduced complexity algorithm, which is an adaptive version of the matching pursuit algorithm, is proposed for the identification of nonlinear systems. The algorithm is demonstrated on various nonlinear systems presented in the literature. The results are favorable compared to other nonlinear identification methods (e.g neural nets). It is demonstrated that the algorithm could be used for the design of adaptive controllers.

关键词： Nonlinear systems Adaptive systems Matching pursuit algorithms Adaptive control pursuit algorithms Vectors Dictionaries Programmable control Adaptive filters Neural networks

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Efficient image representation by anisotropic refinement in matching pursuit

Efficient image representation by anisotropic refinement in ...

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

作者： P. Vandergheynst P. Frossard Signal Processing Laboratory Swiss Federal Institute of Technology Lausanne Switzerland

This paper presents a new image representation method based on anisotropic refinement. It has been shown that wavelets are not optimal to code 2-D objects which need true 2-D dictionaries for efficient approximation. We propose to use rotations and anisotropic scaling to build a real bi-dimensional dictionary. Matching pursuit then stands as a natural candidate to provide an image representation with an anisotropic refinement scheme. It basically decomposes the image as a series of basis functions weighted by their respective coefficients. Even if the basis functions can a priori take any form, bi-dimensional dictionaries are almost exclusively composed of two-dimensional Gabor functions. We present here a new dictionary design by introducing orientation and anisotropic refinement of a Gaussian generating function. The new dictionary permits to efficiently code 2-D objects and more particularly oriented contours. It is shown to clearly outperform common nonoriented Gabor dictionaries.

关键词： Image representation Anisotropic magnetoresistance Matching pursuit algorithms Dictionaries Wavelet transforms Image coding pursuit algorithms Signal processing Laboratories Discrete cosine transforms

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Adaptive image representation with segmented orthogonal matching pursuit

Adaptive image representation with segmented orthogonal matc...

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IEEE International Conference on Image Processing

作者： H.R. Rabiee R.L. Kashyap S.R. Safavian LCC Cellular Institute Arlington VA USA Media & Interconnect Technology Lab Intel Corporation Hillsboro OR USA School of Electrical and Computer Engtineering Purdue University West Lafayette IN USA

In this paper a novel algorithm for adaptive signal expansion is presented. Here the main concern is to efficiently represent the natural images and audio signals. These signals are one or two dimensional signals with unknown or time-varying characteristics. For this type of signal, linear expansion with a fixed set of basis functions is not flexible enough to represent the data with the desired degree of sparseness. We introduce a new algorithm called segmented orthogonal matching pursuit (SOMP). Our experimental results show that the SOMP algorithm is more suitable than the existing signal expansion algorithms for efficient representation of audio and visual information.

关键词： Image representation Image segmentation Matching pursuit algorithms Dictionaries Signal resolution pursuit algorithms Fourier transforms Signal processing Image processing Robustness

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Wavelet projection pursuit for feature extraction and cloud detection in AVIRIS and AVHRR imagery

Wavelet projection pursuit for feature extraction and cloud ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： C.M. Bachmann E.E. Clothiaux D.Q. Luong Airborne Radar Branch Radar Division Naval Research Laboratory Inc. Washington D.C. DC USA Department of Meteorology Pennsylvania State University University Park PA USA Lockheed Martin Arlington VA USA

We examine a class of constrained projection pursuit (PP) algorithms for extracting textural features from multi-spectral remote sensing imagery. Based on the assumption that spatial frequency information is useful for separating classes of interest in the data, topological constraints are defined for the PP filter vectors. The constraint on each filter is imposed by a set of tunable meta-parameters which define each filter as an adaptive Gabor wavelet. We call this approach wavelet projection pursuit (WPP). The application of the approach to cloud detection is described. The long-term goal is to develop algorithms for texture-based cloud masking applicable to future data from the Multi-Angle Imaging Spectrometer (MISR).

关键词： Feature extraction Clouds Gabor filters Adaptive filters pursuit algorithms Data mining Remote sensing Frequency Information filtering Information filters

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Feedback orthogonal pruning pursuit for pulse acquisition in UWB communications

Feedback orthogonal pruning pursuit for pulse acquisition in...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Depeng Yang Husheng Li Gregory D. Peterson Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA

A feedback structure and signal recovery algorithm, orthogonal pruning pursuit, are proposed to apply sequential compressed sensing (CS) on ultra-wideband (UWB) communications. The prior knowledge is exploited by the feedback structure in time sequence UWB signals. The orthogonal pruning pursuit algorithm is utilized to reconstruct UWB echo signals by deleting zero entries to pursuit true non-zero elements. Numerical simulations show that using the proposed scheme, far fewer measurements are needed to achieve good performance compared with other CS algorithms for UWB communications. This saves substantial hardware resources in practical systems.

关键词： Feedback Ultra wideband communication Matching pursuit algorithms pursuit algorithms Sampling methods Pulse modulation Signal reconstruction Reconstruction algorithms Amplitude modulation Compressed sensing

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Automated detection of sleep EEG slow waves based on matching pursuit using a restricted dictionary

Automated detection of sleep EEG slow waves based on matchin...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Antoine Picot Harry Whitmore Florian Chapotot Sleep Metabolism and Health Center University of Chicago

ISBN: (纸本)9781424441211

In this paper, an original method to detect sleep slow waves (SSW) in electroencephalogram (EEG) recordings is proposed. This method takes advantage of a Matching pursuit algorithm using a dictionary reduced to Gabor functions reproducing the main targeted waveform characteristics. By describing the EEG signals in terms of SSW properties, the corresponding algorithm is able to identify waveforms based on the largest matching coefficients. The implemented algorithm was tested on a database of whole night sleep EEG recordings collected in 9 young healthy subjects where SSW have been visually scored by an expert. Besides being fully automated and much faster than visual scoring analysis, the results obtained to the proposed method were in excellent agreement with the expert with 98% of correct detections and a 77% concordance in event time position and duration. These results were superior from those of the classical method both in terms of sensibility and precision.

关键词： eeg sleep matching pursuits SYNCHRONIZING SWITCHES waveforms Dictionaries as Topic Professional personnel Slow waves Electroencephalography pursuit algorithms Automation

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Co-evolutionary computation for constrained min-max problems and its applications for pursuit-evasion games

Co-evolutionary computation for constrained min-max problems...

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Congress on Evolutionary Computation

作者： Jegyom Kim Min-Jea Tahk Department of Aerospace Engineering Korea Air Force Academy South Korea Department of Aerospace Engineering Korea Advanced Institute of Science and Technology Daejeon South Korea

ISBN: (纸本)0780366573

The co-evolutionary computation method for solving constrained min-max problems is proposed. Many engineering problems can be practically expressed as constrained min-max problems. Min-max problems have two groups of variables. Each group will minimize or maximize payoffs and is subject to equality and inequality constraints. Lagrange multipliers are implemented for handling constraints. Primal constrained min-max problems are transformed into dual unconstrained min-max problems by using the Lagrange multipliers. The co-evolutionary computation is used for solving the dual min-max problems. The proposed method deals with separable and inseparable constraints of two groups. The proposed algorithm is applied for pursuit-evasion games with various constraints. Numerical results are compared with those of conventional methods.

关键词： Lagrangian functions Military computing Aerospace engineering Optimization methods Missiles pursuit algorithms Robust control Evolutionary computation Constraint optimization Sun

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Identification of Recurring Wavefront Propagation Patterns in Atrial Fibrillation using Basis pursuit

Identification of Recurring Wavefront Propagation Patterns i...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： S. Zeemering R. Peeters A. van Hunnik S. Verheule U. Schotten Department of Physiology Maastricht University P.O. Box 616 6200 MD Maastricht The

ISBN: (纸本)9781457702150

High density contact electrogram data of atrial fibrillation (AF) contain detailed information on recurring activation patterns and dominant signaling pathways. Current methods to analyze these patterns and pathways rely mainly on supervised atrial deflection annotation and wave reconstruction. In this study, we developed a new algorithm to automatically identify recurring patterns and dominant pathways without the need for annotation. A sparse multivariate autoregression model was estimated on short segments of synchronous unipolar electrograms to extract the dominant interactions between electrograms at different recording electrodes. Sparsity of the electrode interaction matrices at several time-lags was maximized by applying a distance-weighted basis pursuit algorithm. Dominant interactions were identified by computing the mean interaction matrix over a number of consecutive time segments. The algorithm was evaluated on high-density recordings with 234 electrodes and 2.4mm electrode spacing in the left and right atrial free wall of a goat model of AF. The method was able to identify relevant patterns of AF, including wave trains, repetitive breakthrough waves and rotating wave activity.

关键词： Atrial Fibrillation atrial fibrillation autoregressive processes caprine model electrogram Electrodes High density ANNOTATIONS pursuit algorithms Right free wall accessory pathway

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A hierarchical projection pursuit clustering algorithm

A hierarchical projection pursuit clustering algorithm

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International Conference on Pattern Recognition

作者： A.D. Miasnikov J.E. Rome R.M. Haralick Pattern Recognition Lab Department of Computer Science City University of New York New York NY USA

We define a cluster to be characterized by regions of high density separated by regions that are sparse. By observing the downward closure property of density, the search for interesting structure in a high dimensional space can be reduced to a search for structure in lower dimensional subspaces. We present a hierarchical projection pursuit clustering (HPPC) algorithm that repeatedly bi-partitions the dataset based on the discovered properties of interesting 1-dimensional projections. We describe a projection search procedure and a projection pursuit index function based on Cho, Haralick and Yi's improvement of the Kittler and Illingworth optimal threshold technique. The output of the algorithm is a decision tree whose nodes store a projection and threshold and whose leaves represent the clusters (classes). Experiments with various real and synthetic datasets show the effectiveness of the approach.

关键词： Clustering algorithms pursuit algorithms Pattern recognition Computer science Partitioning algorithms Decision trees Shape Binary trees Classification tree analysis Indexing

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