Articles liés à Maximum-Likelihood Deconvolution: A Journey into Model-Based...
Synopsis
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Acheter neuf
Afficher cet article
EUR 48,37
EUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délaisAutres éditions populaires du même titre
Résultats de recherche pour Maximum-Likelihood Deconvolution: A Journey into Model-Based...
Image fournie par le vendeur
Maximum-Likelihood Deconvolution
Edité par
Springer New York, 2011
ISBN 10 : 1461279852
ISBN 13 : 9781461279853
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
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 réf. du vendeur 4190576
Quantité disponible : Plus de 20 disponibles
Image d'archives
Maximum-Likelihood Deconvolution: A Journey into Model-Based Signal Processing (Signal Processing and Digital Filtering)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. In. N° de réf. du vendeur ria9781461279853_new
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Maximum-Likelihood Deconvolution
Edité par
Springer New York, Springer New York Sep 2011, 2011
ISBN 10 : 1461279852
ISBN 13 : 9781461279853
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 244 pp. Englisch. N° de réf. du vendeur 9781461279853
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Maximum-Likelihood Deconvolution : A Journey into Model-Based Signal Processing
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
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 réf. du vendeur 9781461279853
Quantité disponible : 1 disponible(s)
Image d'archives
Maximum-Likelihood Deconvolution: A Journey into Model-Based Signal Processing
Edité par
Springer-Verlag New York Inc., 2011
ISBN 10 : 1461279852
ISBN 13 : 9781461279853
Neuf
Paperback / softback
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 378. N° de réf. du vendeur C9781461279853
Quantité disponible : Plus de 20 disponibles
Image d'archives
Maximum-likelihood Deconvolution: A Journey into Modelbased Signal Processing (Signal Processing and Digital Filtering)
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : Brand New. reprint edition. 241 pages. 9.25x6.10x0.60 inches. In Stock. N° de réf. du vendeur x-1461279852
Quantité disponible : 2 disponible(s)
Image d'archives
Maximum-Likelihood Deconvolution: A Journey into Model-Based Signal Processing (Signal Processing and Digital Filtering)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur ABLIING23Mar2716030029322
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Maximum-Likelihood Deconvolution
Edité par
Springer New York Sep 2011, 2011
ISBN 10 : 1461279852
ISBN 13 : 9781461279853
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
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 réf. du vendeur 9781461279853
Quantité disponible : 2 disponible(s)
Image d'archives
Maximum-Likelihood Deconvolution: A Journey into Model-Based Signal Processing (Signal Processing and Digital Filtering)
Edité par
Springer, 2011
ISBN 10 : 1461279852
ISBN 13 : 9781461279853
Ancien ou d'occasion
Paperback
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
Paperback. Etat : Like New. Like New. book. N° de réf. du vendeur ERICA77314612798526
Quantité disponible : 1 disponible(s)