9781107619289-1107619289-Bayesian Filtering and Smoothing (Institute of Mathematical Statistics Textbooks)

Bayesian Filtering and Smoothing (Institute of Mathematical Statistics Textbooks)

ISBN-13: 9781107619289
ISBN-10: 1107619289
Edition: 1
Author: Sarkka, Simo
Publication date: 2013
Publisher: Cambridge University Press
Format: Paperback 256 pages
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Book details

ISBN-13: 9781107619289
ISBN-10: 1107619289
Edition: 1
Author: Sarkka, Simo
Publication date: 2013
Publisher: Cambridge University Press
Format: Paperback 256 pages

Summary

Acknowledged authors Sarkka, Simo wrote Bayesian Filtering and Smoothing (Institute of Mathematical Statistics Textbooks) comprising 256 pages back in 2013. Textbook and eTextbook are published under ISBN 1107619289 and 9781107619289. Since then Bayesian Filtering and Smoothing (Institute of Mathematical Statistics Textbooks) textbook was available to sell back to BooksRun online for the top buyback price or rent at the marketplace.

Description

Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). Interest in these methods has exploded in recent years, with numerous applications emerging in fields such as navigation, aerospace engineering, telecommunications and medicine. This compact, informal introduction for graduate students and advanced undergraduates presents the current state-of-the-art filtering and smoothing methods in a unified Bayesian framework. Readers learn what non-linear Kalman filters and particle filters are, how they are related, and their relative advantages and disadvantages. They also discover how state-of-the-art Bayesian parameter estimation methods can be combined with state-of-the-art filtering and smoothing algorithms. The book's practical and algorithmic approach assumes only modest mathematical prerequisites. Examples include MATLAB computations, and the numerous end-of-chapter exercises include computational assignments. MATLAB/GNU Octave source code is available for download at www.cambridge.org/sarkka, promoting hands-on work with the methods.

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