An Introduction to Kalman Filtering with MATLAB Examples (Synthesis Lectures on Signal Processing)

Kovvali, Narayan; Banavar, Mahesh; Spanias, Andreas

ISBN 10: 3031014081 ISBN 13: 9783031014086

Edit� par Springer, 2013

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The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems. The purpose of this book is to present a brief introduction to Kalman filtering. The theoretical framework of the Kalman filter is first presented, followed by examples showing its use in practical applications. Extensions of the method to nonlinear problems and distributed applications are discussed. A software implementation of the algorithm in the MATLAB programming language is provided, as well as MATLAB code for several example applications discussed in the manuscript.

� propos de l?auteur: Nasser Kehtarnavaz is a Professor of Electrical Engineering at the University of Texas at Dallas. He has written four other books and numerous papers pertaining to signal and image processing, and regularly teaches undergraduate and graduate signal and image processing courses. Among his many professional activities, he is currently serving as Coeditor-in-Chief of Journal of Real-Time Image Processing, and Chair of the Dallas Chapter of the IEEE Signal Processing Society. Dr. Kehtarnavaz is a Fellow of SPIE, a Senior Member of IEEE, and a Professional Engineer. Shane Parris received his B.S. in Electrical Engineering from University of Texas at Dallas in 2013. His research interests include signal and image processing, and real-time implementation of signal and image processing algorithms. Abhishek Sehgal received his B.E. in Instrumentation Technology from Visvesvaraya Technological University in India in 2012, his M.S. and Ph.D. in Electrical Engineering at the University of Texas at Dallas in 2015 and 2019, respectively. His research interests include signal and image processing, and real-time implementation of signal and image processing algorithms.

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Titre : An Introduction to Kalman Filtering with ...
�diteur : Springer
Date d'�dition : 2013
Reliure : Couverture souple
Etat : New

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An Introduction to Kalman Filtering with MATLAB Examples (Synthesis Lectures on Signal Processing)

Kovvali, Narayan,Banavar, Mahesh,Spanias, Andreas

Edit� par Springer, 2013

ISBN 10 : 3031014081 ISBN 13 : 9783031014086

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An Introduction to Kalman Filtering with MATLAB Examples

Kovvali, Narayan|Banavar, Mahesh|Spanias, Andreas

Edit� par Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer, 2013

ISBN 10 : 3031014081 ISBN 13 : 9783031014086

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Kartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman. N� de r�f. du vendeur 608129584

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An Introduction to Kalman Filtering with MATLAB Examples

Narayan Kovvali (u. a.)

Edit� par Springer International Publishing, 2013

ISBN 10 : 3031014081 ISBN 13 : 9783031014086

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An Introduction to Kalman Filtering with MATLAB Examples

Narayan Kovvali

Edit� par Springer International Publishing, Springer International Publishing, 2013

ISBN 10 : 3031014081 ISBN 13 : 9783031014086

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems. The purpose of this book is to present a brief introduction to Kalman filtering. The theoretical framework of the Kalman filter is first presented, followed by examples showing its use in practical applications. Extensions of the method to nonlinear problems and distributed applications are discussed. A software implementation of the algorithm in the MATLAB programming language is provided, as well as MATLAB code for several example applications discussed in the manuscript. N� de r�f. du vendeur 9783031014086

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An Introduction to Kalman Filtering with MATLAB Examples

Narayan Kovvali

Edit� par Springer International Publishing, Springer International Publishing Okt 2013, 2013

ISBN 10 : 3031014081 ISBN 13 : 9783031014086

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Taschenbuch. Etat : Neu. Neuware -The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems. The purpose of this book is to present a brief introduction to Kalman filtering. The theoretical framework of the Kalman filter is first presented, followed by examples showing its use in practical applications. Extensions of the method to nonlinear problems and distributed applications are discussed. A software implementation of the algorithm in the MATLAB programming language is provided, as well as MATLAB code for several example applications discussed in the manuscript.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 84 pp. Englisch. N� de r�f. du vendeur 9783031014086

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An Introduction to Kalman Filtering with MATLAB Examples

Narayan Kovvali

Edit� par Springer International Publishing Okt 2013, 2013

ISBN 10 : 3031014081 ISBN 13 : 9783031014086

Neuf Taschenbuch

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems. The purpose of this book is to present a brief introduction to Kalman filtering. The theoretical framework of the Kalman filter is first presented, followed by examples showing its use in practical applications. Extensions of the method to nonlinear problems and distributed applications are discussed. A software implementation of the algorithm in the MATLAB programming language is provided, as well as MATLAB code for several example applications discussed in the manuscript. 84 pp. Englisch. N� de r�f. du vendeur 9783031014086

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