Bayesian Filtering and Smoothing

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Bayesian Filtering and Smoothing

By Simo Särkkä

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This compact, informal introduction for graduate students and advanced undergraduates draws together modern state estimation methods including non-linear Kalman filters, particle filters, and the related smoothing algorithms. Its practical and algorithmic approach assumes only modest mathematical prerequisites. End-of-chapter exercises include computational assignments, and Matlab code is available for download.

Subject: Mathematics & Statistics -> Mathematics -> Probability

Bayesian Filtering and Smoothing
1st edition
Publisher: Cambridge University Press 9/5/13
Imprint: Cambridge University Press
Language: English

ISBN 10: 110742433X
ISBN 13: 9781107424333
Print ISBN: 9781107030657

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