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Bayesian Filtering and Smoothing by Simo Sarkka (Paperback, 2013)

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About this product

Product Information

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 code is available for download at www.cambridge.org/sarkka, promoting hands-on work with the methods.

Product Identifiers

Publisher
Cambridge University Press
ISBN-13
9781107619289
eBay Product ID (ePID)
184396881

Product Key Features

Author
Simo Sarkka
Publication Name
Bayesian Filtering and Smoothing
Format
Paperback
Language
English
Subject
Mathematics
Publication Year
2013
Type
Textbook
Number of Pages
252 Pages

Dimensions

Item Height
226mm
Item Width
150mm
Item Weight
420g

Additional Product Features

Title_Author
Simo Sarkka
Series Title
Institute of Mathematical Statistics Textbooks
Country/Region of Manufacture
United Kingdom

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