Introduction to Optimal Estimation (Advanced Textbooks in Control and Signal Processing)

Kamen, Edward W.; Su, Jonathan K.

ISBN 10: 185233133X ISBN 13: 9781852331337

Editorial: Springer, 1999

Idioma: Ingl�s

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Descripci�n

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Detalles bibliogr�ficos

T�tulo

Introduction to Optimal Estimation (Advanced Textbooks in Control and Signal Processing)

Editor

Springer

Fecha de publicaci�n

1999

Idioma

Ingl�s

ISBN 10

185233133X

ISBN 13

9781852331337

Encuadernaci�n

Encuadernaci�n de tapa blanda

Estado

New

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Sinopsis

A handy technical introduction to the latest theories and techniques of optimal estimation. It provides readers with extensive coverage of Wiener and Kalman filtering along with a development of least squares estimation, maximum likelihood and maximum a posteriori estimation based on discrete-time measurements. Much emphasis is placed on how they interrelate and fit together to form a systematic development of optimal estimation. Examples and exercises refer to MATLAB software.

De la contraportada

This book, developed from a set of lecture notes by Professor Kamen, and since expanded and refined by both authors, is an introductory yet comprehensive study of its field. It contains examples that use MATLAB^� and many of the problems discussed require the use of MATLAB^�. The primary objective is to provide students with an extensive coverage of Wiener and Kalman filtering along with the development of least squares estimation, maximum likelihood estimation and a posteriori estimation, based on discrete-time measurements. In the study of these estimation techniques there is strong emphasis on how they interrelate and fit together to form a systematic development of optimal estimation. Also included in the text is a chapter on nonlinear filtering, focusing on the extended Kalman filter and a recently-developed nonlinear estimator based on a block-form version of the Levenberg-Marquadt Algorithm.

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