Bayesian Filtering and Smoothing |
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Author:
| Särkkä, Simo |
Series title: | Institute of Mathematical Statistics Textbooks Ser. |
ISBN: | 978-1-107-03065-7 |
Publication Date: | Sep 2013 |
Publisher: | Cambridge University Press
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Book Format: | Hardback |
List Price: | USD $110.00 |
Book Description:
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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.
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.