Results 281 to 290 of about 261,559 (305)

Linear processing of nonuniformly sampled signals

[1991] Proceedings of the 34th Midwest Symposium on Circuits and Systems, 2002
The authors describe a novel approach, based on a coordinate transformation, that can process nonuniformly sampled signals efficiently, in the sense that the number of computations for processing the nonuniformly spaced data will be the same as in the uniform sampling case for the same number of samples in both cases. In situations where the nonuniform
Y. Feria, J. McPherson
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Free Probability, Sample Covariance Matrices, and Signal Processing

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006
Free probability provides tools and techniques for analyzing the eigen-spectra of large Hermitian random matrices. These stochastic eigen-analysis techniques have been invaluable in providing insight into the structure of sample covariance matrices. We briefly outline how these techniques can be used to analytically predict the spectrum of large sample
N. Raj Rao, Alan Edelman
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Multiscale statistical signal processing: identification of a multiscale AR process from a sample of an ordinary signal

IEEE Transactions on Signal Processing, 1993
Summary: The theory of stochastic processes on homogeneous trees aims at contributing to the theory of multiresolution stochastic modeling and associated techniques of multiscale, statistical signal processing. In this paper, we solve the problem of identifying such a multiscale process indexed by the nodes of a tree from the observation of this ...
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The Sampling Theorem of Signal Processing

2002
This overview paper treats the sampling theorem of signal analysis, and especially a variety of its applications in mathematics. These include fractional and infinite series forms of classical combinatorial identities, such as the Chu-Vandermonde convolution formula and some identities due to Hagen, the Gauss summation formula for hypergeometric ...
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Signal processing on graphs: Case of sampling in Paley–Wiener spaces

Signal Processing, 2018
Abstract Given a weighted undirected graph, this paper focuses on the sampling problem of uniquely recovering Paley–Wiener functions from a sampled set of vertices. In accordance with the measures of connectivity introduced by Pesenson [30], we address two optimization problems related to discrete sampling on graphs via the so-called uniqueness sets,
Borodin, Valeria, Snoussi, Hichem, Hnaien, Faicel, Labadie, Nacima   +3 more
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Sampling and optimum data processing of detector signals

Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1992
Abstract The optimum processing of data, obtained by sampling detector signals, is developed for signals known a priori in shape, their time of occurrence and amplitude being unknown. The processing is based on the maximum-likelihood method. The resolutions in the time and amplitude estimations of the pulse are compared with those obtained from an ...
BERTUCCIO, GIUSEPPE, GATTI, EMILIO, SAMPIETRO, MARCO, P. Rehak, S. Rescia   +4 more
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Changeable sampling processing for chirp signals in the SAR

ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344), 2002
Aimed at the chirp signal resulting from a moving target in SAR, this paper puts forward a signal processing method for changing sample ratios and gives theoretical analyses and the results of a simulation experiment. The results show that the method is very effective, practical and clearly separates a moving target, especially a slow-moving target.
null Wang Shengli, null Zhu Li
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The Evolution of Analogue Sampled-Data Signal Processing

1993
In this chapter the evolution of analogue sampled-data techniques has been reviewed. The switched-capacitor technique has been seen to dominate in general purpose applications, whilst CCDs are being used extensively in imaging arrays. The emergence of mixed-mode analogue and digital signal processing and the subsequent need to integrate analogue ...
Nicholas C. Battersby, Chris Toumazou
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Importance sampling in signal processing applications

2015
Importance sampling is a technique originating in Monte Carlo simulation whereby one samples from a different, weighted distribution, in order to reduce variance of the resulting estimator. More recently, variations of importance sampling have emerged as a means for reducing computational and sample complexity in different problems of modern signal ...
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Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR

Progress in Nuclear Magnetic Resonance Spectroscopy, 2014
Mehdi Mobli, Jeffrey C Hoch
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