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

Kamen, Edward W.

ISBN 10: 185233133X / ISBN 13: 9781852331337

Editore: Springer, 1999

Riguardo questo articolo

This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:9781852331337.

Codice articolo 7098111

Dati bibliografici

• Titolo: Introduction to Optimal Estimation (Advanced Textbooks in Control and Signal Processing)
• Editore: Springer
• Data di pubblicazione: 1999
• Lingua: Inglese
• ISBN 10: 185233133X
• ISBN 13: 9781852331337
• Rilegatura: Brossura
• Condizione: Fair
• Peso: 700 grammi
• Cataloghi dei venditori:
  • Engineering

Descrizione articolo

Riassunto

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.

Dalla quarta di copertina

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.