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检索条件"任意字段=Advanced Signal Processing Algorithms, Architectures, and Implementations II"

共 465 条记录，以下是171-180 订阅

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APPLICATION OF THE WIGNER DISTRIBUTION TO THE DETECTION OF LATE POTENTIALS IN ECG

APPLICATION OF THE WIGNER DISTRIBUTION TO THE DETECTION OF L...

引用

CONF ON advanced signal processing algorithms, architectures, AND implementations 3

作者： PEYRIN, F KAROUBI, B MORLET, D DUPONT, F RUBEL, P DESSEIGNE, P TOUBOUL, P Lab. de Traitement du Signal et Ultrasons (France) INSERM/Lyon (France) Lab. Traitement du Signal et Ultrasons (France) Hopital Cardiologique (France)

ISBN: (纸本)081940943X

The problem of detecting micropotentials in high resolution ECGs is of great importance to predict ventricular tachycardia. Since both conventional time domain and frequential domain methods present serious limitations, we address this problem using a high resolution time frequency method. The possibilities of the spectrogram and Wigner distribution (WD) are evaluated in order to analyze ECGs acquired both on patients with and without ventricular tachycardia. Furthermore, quantitative features are extracted from those representations in order to discriminate the two classes.

关键词： Electrocardiography Time-frequency analysis signal analyzers Feature extraction Convolution Smoothing Electronic filtering Fourier transforms Heart Linear filtering

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Parallel implementation of a face location algorithm on DSP's with SynDEx environment

Parallel implementation of a face location algorithm on DSP'...

引用

Conference on advanced signal processing algorithms, architectures, and implementations IX

作者： Yang, F Paindavoine, M Abdi, H Univ Burgundy Lab Le2i Fac Sci Mirande F-21011 Dijon France

ISBN: (纸本)0819432938

The aim of our work is to implement a system of automatic face image processing on DSP's : face detection in an image, face recognition and face identification. The first step is to localize the face in an image. Our approach consists to approximate the face oval shape with an ellipse and to compute coordinates of the center of the ellipse. For this purpose, we explore a new version of the Hough transformation : the Fuzzy Generalized Hough transformation. To reduce the computation time, we present also several parallel implementations of the algorithm on a multi-DSP architecture using SynDEx tool which is a programming environment to generate optimized distributed real-time executives. We show that an acceleration of factor 1.7 has been obtained.

关键词： automatic face image processing face location edge detection Hough transformation efficient mapping algorithm and architecture A(3) methodology SynDEx

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CUMULANT BASED STATIONARY AND NONSTATIONARY MODELS FOR CLASSIFICATION AND SYNTHESIS OF RANDOM-FIELDS

CUMULANT BASED STATIONARY AND NONSTATIONARY MODELS FOR CLASS...

引用

CONF ON advanced signal processing algorithms, architectures, AND implementations 3

作者： ZHOU, GT GIANNAKIS, GB Univ. of Virginia (United States)

ISBN: (纸本)081940943X

Cumulants are employed for classification and synthesis of textured images because they suppress additive Gaussian noise of unknown covariance and are capable of resolving phase and causality issues in stationary non-Gaussian random fields. Their performance is compared with existing autocorrelation based approaches which offer sample estimates of smaller variance and lower computational complexity. Nonlinear matching techniques improve over linear equation methods in estimating parameters of non-Gaussian random fields especially under model mismatch. Seasonal 1-D sequences allow for semi-stationary 2-D models and their performance is illustrated on synthetic space variant textures. The potential of prolate spheroidal basis expansion is also described for parsimonious nonstationary modeling of space variant textured images.

关键词： Autoregressive models Image classification Statistical analysis Image segmentation Statistical modeling Image processing signal to noise ratio Performance modeling Radon signal processing

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Space-time beamforming for randomly distributed sensors

Space-time beamforming for randomly distributed sensors

引用

SPIE Conference on advanced signal processing algorithms, architectures, and implementations ViiI

作者： Yao, K Hudson, RE Reed, CW Chen, D Tung, TL Lorenzelli, F Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA

ISBN: (纸本)0819429163

We briefly review the signal processing architecture of a wireless MEM sensor system for source detection, signal enhancement, localization, and identification. A blind beamformer using only the measured data of randomly distributed sensors to form a sample correlation matrix is proposed. The maximum power collection criterion is used to obtain array weights from the dominant eigenvector of the sample correlation matrix. An effective blind beamforming estimation of the time delays of the dominant source is demonstrated. Source localization based on a novel least-squares method for time delay estimation is also given. Array system performance based on analysis, simulation, and measured acoustical/seismic sensor data is presented. Applications of such a system to multimedia, intrusion detection, and surveillance are briefly discussed.

关键词： random array array processing beamforming space-time filtering MEM sensor sensor network

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TOMOGRAPHIC IMAGING OF THE IONOSPHERE USING BIDIRECTIONAL EXTRAPOLATION ALGORITHM 4

TOMOGRAPHIC IMAGING OF THE IONOSPHERE USING BIDIRECTIONAL EX...

引用

4TH CONF ON advanced signal processing algorithms, architectures, AND implementations

作者： NA, HR LEE, H SHEN, J Univ. of Iowa (United States) Univ. of California/Santa Barbara (United States)

ISBN: (纸本)0819412767

In this paper, a new Fourier domain reconstruction algorithm is presented which utilizes the information contained in the known region of the spectrum to estimate the frequency samples in the missing-cone area. Unlike conventional two-dimensional extrapolation techniques, this method uses bi-directional extrapolation to maximize the amount of known information in each extrapolation step. By fully utilizing the information of the measured data, the resulting image provides a more accurate estimation of the electron density distribution. The resolution improvement achieved is mainly due to the proper utilization of the available information in the measurements during the image formation process.

关键词： Tomography Statistical analysis Data acquisition Reconstruction algorithms Image processing Satellites Image resolution Image acquisition signal detection Computer engineering

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Comparison of time-frequency signal analysis techniques with application to speech recognition

Comparison of time-frequency signal analysis techniques with...

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advanced signal processing algorithms, architectures, and implementations iiI

作者： Reilly, Andrew P. Boashash, Boualem Queensland Univ. of Technology Brisbane Queensland Australia

ISBN: (纸本)081940943X

Techniques for machine recognition of speech exist, but use representations of the speech signal which cannot convey some of the speech information. Alternatives from time-frequency and time-scale analysis are compared with the traditional methods with a view to improving the word recognition rate. Experiments have shown the speech recognition rate improves in some cases.

关键词： Speech recognition

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A unified Bayesian framework for algorithms to recover blocky signals

A unified Bayesian framework for algorithms to recover block...

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Conference on advanced signal processing algorithms, architectures, and implementations XVii

作者： Calvetti, Daniela Somersalo, Erkki Case Western Reserve Univ Dept Math Cleveland OH 44106 USA Case Western Reserve Univ Ctr Modeling Integrated Metab Syst Cleveland OH 44106 USA Aalto Univ Dept Math Helsinki Finland

ISBN: (纸本)9780819468451

We consider the problem of recovering signals from noisy indirect observations under the additional a priori information that the signal is believed to be slowly varying except at all unknown number of points where it may have discontinuities of unknown size. The model problem is a linear deconvolution problem. To take advantage of the qualitative prior information available, we use a non-stationary Markov model with the variance of the innovation process also unknown, and apply Bayesian techniques to estimate both the signal and the prior variance. We propose a fast iterative method for computing a MAP estimates and we show that, with a rather standard choices of the hyperpriors, the algorithm produces the fixed point iterative solutions of the total variation and of the Perona-Malik regularization methods. We also demonstrate that, unlike the non-statistical estimation methods, the Bayesian approach leads to a very natural reliability assessment of edge detection by a Markov Chain Monte Carlo (MCMC) based analysis of the posterior.

关键词： signal processing Data modeling Reliability Stochastic processes Atrial fibrillation Autoregressive models Deconvolution Monte Carlo methods Statistical analysis Mathematics

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A multivariate speech activity detector based on the syllable rate

A multivariate speech activity detector based on the syllabl...

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SPIE Conference on advanced signal processing algorithms, architectures, and implementations ViiI

作者： Smith, D Townsend, J Nelson, DJ US Dept Def Ft George G Meade MD 20755 USA

ISBN: (纸本)0819429163

Computationally efficient algorithms which perform speech activity detection have significant potential economic and labor saving benefit, by automating an extremely tedious manual process. In many applications, it is desirable to extract intervals of speech which are bounded by segments of other signal types (fax/modem, music, static, dial tones, etc.). In the past, algorithms which successfully discriminate between speech and one specific other signal type have been developed. Frequently, these algorithms fail when the specific non-speech signal is replaced by a different non-speech signal. Little work has been done on combining such discriminators in order to solve the general speech vs. non-speech discrimination problem. Typically, several signal specific discriminators are blindly combined with predictable negative results. Moreover, when a large number of discriminators are involved, dimension reduction is achieved using Principal Components, which optimally compresses signal variance into the fewest number of dimensions. Unfortunately, these new coordinates are not necessarily optimal for discrimination. In this paper we apply graphical tools to determine a set of discriminators which produce excellent speech vs. non-speech clustering, thereby eliminating the guesswork in selecting good feature vectors. This cluster structure provides a basis for a general multivariate speech vs. non-speech discriminator, which compares very favorably with the TALKATIVE speech extraction algorithm.

关键词： signal processing

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Optimal inversions of uncertain matrices - an estimation and control perspective

Optimal inversions of uncertain matrices - an estimation and...

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Conference on advanced signal processing algorithms architectures and implementations XiiI

作者： Tao, KM SRI Int Menlo Pk CA 94025 USA

ISBN: (纸本)0819450782

Many system and signal related problems involve matrix inversion of some kind. For example, in estimation and signal recovery applications, inversion of the channel response matrix is often required in order to estimate the source signals. In the control of multivariable systems, inverting a process gain matrix may be called for in order to deliver appropriate control actions. There are situations where these matrices should be considered as uncertain (or random): for example, when the process/channel environments vary randomly, or when significant uncertainties are involved in estimating these matrices. Based on a unified approach, this paper considers both the right inversion (for control) and the left inversion (for estimation) of random matrices. In both cases, minimizing a statistical error function leads to the determination of optimal or linear optimal inversion. Connections with related techniques, such as the total least squares (TLS), the ridge regression, the Levenberg-Marquardt algorithm and the regularization theory are discussed. A variant Kalman filtering problem with randomly varying measurement gain matrix is among the applications addressed. Monte Carlo simulation results show substantial benefits by taking process/model uncertainty into consideration.

关键词： statistical inversion of uncertain matrices signal processing estimation control Kalman filtering with random measurement matrix channel equalization

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TIME-VARYING POLYSPECTRA AND REDUCED WIGNER-VILLE TRISPECTRUM

TIME-VARYING POLYSPECTRA AND REDUCED WIGNER-VILLE TRISPECTRU...

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CONF ON advanced signal processing algorithms, architectures, AND implementations 3

作者： BOASHASH, B RISTIC, B Queensland Univ. of Technology (Australia)

ISBN: (纸本)081940943X

This paper consists of two parts. The first part reviews a class of higher-order Wigner-Ville distributions projected onto a single frequency axis. This class is referred to as polynomial Wigner-Ville distributions (PWVDs). For random processes, the expected value of PWVDs represent time-varying higher-order moment spectra. The second part defines and studies a particular member of a class of time-varying higher-order spectra based on PWVDs, namely a reduced Wigner-Ville trispectrum (RWVT). This novel time-frequency representation is shown to be a very efficient tool for analysis of FM signals affected by Gaussian amplitude modulation. In the paper, we present a statistical comparison of the RWVT and WVD based instantaneous frequency estimates for linear FM signals in absence and in presence of multiplicative noise. For multicomponent signals, the RWVT has to be re-defined and calculated in the full multi-lag domain.

关键词： Fermium Frequency modulation Interference (communication) signal to noise ratio Time-frequency analysis Modulation signal processing Statistical analysis Amplitude modulation signal analyzers

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