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

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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

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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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Application of higher-order cepstral techniques in problems of fetal heart signal extraction 6

Application of higher-order cepstral techniques in problems ...

引用

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

作者： SabryRizk, M Zgallai, W Hardiman, P ORiordan, J CITY UNIV LONDON DEPT ELECT ENGNSIGNAL PROC GRPLONDON EC1V 0HBENGLAND

ISBN: (纸本)0819422347

Recently, cepstral analysis based on second order statistics and homomorphic filtering techniques have been used in the adaptive decomposition of overlapping, or otherwise, and noise contaminated ECG complexes of mothers and fetals obtained by a transabdominal surface electrodes connected to a monitoring instrument, an interface card, and a PC. Differential time delays of fetal heart beats measured from a reference point located on the mother complex after transformation to cepstra domains are first obtained and this is followed by fetal heart rate variability computations. Homomorphic filtering in the complex cepstral domain and the subuent transformation to the time domain results in fetal complex recovery. However, three problems have been identified with second-order based cepstral techniques that needed rectification in this paper. These are (1) errors resulting from the phase unwrapping algorithms and leading to fetal complex perturbation, (2) the unavoidable conversion of noise statistics from Gaussianess to non-Gaussianess due to the highly non-linear nature of homomorphic transform does warrant stringent noise cancellation routines, (3) due to the aforementioned problems in (1) and (2), it is difficult to adaptively optimize windows to include all individual fetal complexes in the time domain based on amplitude thresholding routines in the complex cepstral domain (i.e. the task of `zooming' in on weak fetal complexes requires more processing time). The use of third-order based high resolution differential cepstrum technique results in recovery of the delay of the order of 120 milliseconds.

关键词： advanced signal processing techniques non-linear adaptive filtering differential bicepstral applications non-invasive fetal ECG monitoring

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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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TRUNCATED SAMPLING FOR THE FOURIER-MELLIN TRANSFORM WITH APPLICATIONS TO WIDE-BAND WvD COMPUTATION

TRUNCATED SAMPLING FOR THE FOURIER-MELLIN TRANSFORM WITH APP...

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

作者： ALLEN, JC Naval Ocean Systems Ctr. (United States)

ISBN: (纸本)0819404098

The Fourier-Mellin transform (FMT) of an input function is defined as and is the magnitude squared of the Mellin transform of the magnitude squared of the Fourier transform of the input function [1]. As such the FMT is unchanged by translations and dilations of the input function. While the FMT has found applications in optical pattern recognition [3] [5] ship classification by sonar and radar [15] and image processing [10] only cursory attention has been paid to the truncation error incurred by using a finite number of samples of the input function. This paper establishes truncation bounds for computing the FMT for band-limited functions from a finite number of samples of the input function. These bounds naturally suggest an implementation of the FMT by the method of direct expansions [4] [14]. This approach readily generalizes to a direct expansion for the Wigner-ville distribution [13] and the Q distribution [2]. 1 Principal Notation u(x) fff00 e_2tu(t)dt Fourier transform of u M(u s) fD X_i2r8() Mellin transform of u . FM(u s) M(lI(x)I2 s)________ Fourier-Mellin transform of u Q(U v f002rt U(wft)_v(w/fr) Q distribution of U and v W(U v t w) fe_i2ntY U(w + y/2) v(w y/2) dy Wigner-ville distribution of U and v

关键词： Fourier transforms Error analysis Image classification Image processing Optical pattern recognition Radar

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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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Simultaneous operation of two over-the-horizon radars

Simultaneous operation of two over-the-horizon radars

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

作者： Zhang, YM Frazer, GJ Amin, MG Villanova Univ Ctr Adv Commun Villanova PA 19085 USA Def Sci & Technol Org Intelligence Surveillance & Reconnaissance Div Edinburgh SA 5111 Australia

ISBN: (纸本)0819454974

Over the horizon radar (OTHR) is a well developed sensor technology in established use for long-range air and surface surveillance. More detailed information about the targets can be achieved by using simultaneous operation of multiple OTHRs. However, a key limitation with HF radar is the conflict between selection of an appropriate operating frequency and the demand for radar waveform bandwidth commensurate with the range resolution requirement of the radar. In this paper, we consider the simultaneous operation of two over-the-horizon radar systems that use the same frequency band with different chirp waveforms to respond the advanced wide-area surveillance needs without reducing, the pulse repetitive frequency. A cross-radar interference cancellation technique is proposed and shown to be effective.

关键词： Radar Doppler effect Receivers Surveillance Time-frequency analysis Fermium Frequency modulation signal processing Knowledge management Sensor technology

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