Introduction to Optimal Estimation - Advanced Textbooks in Control and Signal Processing

4.00 ( 1 Ratings by Goodreads)
Introduction to Optimal Estimation

Introduction to Optimal Estimation - Advanced Textbooks in Control and Signal Processing

4.00 (1 Ratings by Goodreads)
paperback
Published: 30 September, 1999
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Description

Developed from a set of lecture notes by Professor Kamen and since developed and refined by both authors, this introductory yet comprehensive study is a prime example in its field. There are examples in the book that use MATLAB® and many of the problems discussed require the use of MATLABâ. 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 maximum a posteriori estimation, based on discrete-time measurements. In the study of these estimation techniques there is a 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-Marquardt algorithm.

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More Details

Type Book
ISBN13 9781852331337
ISBN10 9781852331
Number Of Pages 380
Item Weight 1000 g
Publisher / Reseller Springer London Ltd
Format paperback
Edition 1999 ed.
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