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Maximum-Likelihood Deconvolution : A Journey into Model-Based Signal Processing

Jerry M. Mendel

Edit� par Springer New York, 2011

ISBN 10 : 1461279852 ISBN 13 : 9781461279853

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Convolution is the most important operation that describes the behavior of a linear time-invariant dynamical system. Deconvolution is the unraveling of convolution. It is the inverse problem of generating the system's input from knowledge about the system's output and dynamics. Deconvolution requires a careful balancing of bandwidth and signal-to-noise ratio effects. Maximum-likelihood deconvolution (MLD) is a design procedure that handles both effects. It draws upon ideas from Maximum Likelihood, when unknown parameters are random. It leads to linear and nonlinear signal processors that provide high-resolution estimates of a system's input. All aspects of MLD are described, from first principles in this book. The purpose of this volume is to explain MLD as simply as possible. To do this, the entire theory of MLD is presented in terms of a convolutional signal generating model and some relatively simple ideas from optimization theory. Earlier approaches to MLD, which are couched in the language of state-variable models and estimation theory, are unnecessary to understand the essence of MLD. MLD is a model-based signal processing procedure, because it is based on a signal model, namely the convolutional model. The book focuses on three aspects of MLD: (1) specification of a probability model for the system's measured output; (2) determination of an appropriate likelihood function; and (3) maximization of that likelihood function. Many practical algorithms are obtained. Computational aspects of MLD are described in great detail. Extensive simulations are provided, including real data applications. N� de r�f. du vendeur 9781461279853

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Maximum-likelihood Deconvolution: A Journey into Modelbased Signal Processing (Signal Processing and Digital Filtering)

Jerry M. Mendel

Edit� par Springer New York, 2012

ISBN 10 : 1461279852 ISBN 13 : 9781461279853

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Paperback. Etat : Brand New. reprint edition. 241 pages. 9.25x6.10x0.60 inches. In Stock. N� de r�f. du vendeur x-1461279852

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Maximum-Likelihood Deconvolution

Jerry M. Mendel

Edit� par Springer New York, 2011

ISBN 10 : 1461279852 ISBN 13 : 9781461279853

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Convolution is the most important operation that describes the behavior of a linear time-invariant dynamical system. Deconvolution is the unraveling of convolution. It is the inverse problem of generating the system s input from knowledge about the system s. N� de r�f. du vendeur 4190576

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Maximum-Likelihood Deconvolution: A Journey into Model-Based Signal Processing (Signal Processing and Digital Filtering)

Mendel, Jerry M.

Edit� par Springer, 2011

ISBN 10 : 1461279852 ISBN 13 : 9781461279853

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Maximum-Likelihood Deconvolution

Jerry M. Mendel

Edit� par Springer New York Sep 2011, 2011

ISBN 10 : 1461279852 ISBN 13 : 9781461279853

Neuf Taschenbuch

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Convolution is the most important operation that describes the behavior of a linear time-invariant dynamical system. Deconvolution is the unraveling of convolution. It is the inverse problem of generating the system's input from knowledge about the system's output and dynamics. Deconvolution requires a careful balancing of bandwidth and signal-to-noise ratio effects. Maximum-likelihood deconvolution (MLD) is a design procedure that handles both effects. It draws upon ideas from Maximum Likelihood, when unknown parameters are random. It leads to linear and nonlinear signal processors that provide high-resolution estimates of a system's input. All aspects of MLD are described, from first principles in this book. The purpose of this volume is to explain MLD as simply as possible. To do this, the entire theory of MLD is presented in terms of a convolutional signal generating model and some relatively simple ideas from optimization theory. Earlier approaches to MLD, which are couched in the language of state-variable models and estimation theory, are unnecessary to understand the essence of MLD. MLD is a model-based signal processing procedure, because it is based on a signal model, namely the convolutional model. The book focuses on three aspects of MLD: (1) specification of a probability model for the system's measured output; (2) determination of an appropriate likelihood function; and (3) maximization of that likelihood function. Many practical algorithms are obtained. Computational aspects of MLD are described in great detail. Extensive simulations are provided, including real data applications. 244 pp. Englisch. N� de r�f. du vendeur 9781461279853

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