Bayesian filtering and smoothing / Simo Särkkä.

Format:

Book

Author/Creator:

Särkkä, Simo.

Series:

Institute of Mathematical Statistics textbooks ; 3.

Institute of Mathematical Statistics textbooks ; 3

Language:

English

Subjects (All):

Bayesian statistical decision theory.

Filters (Mathematics).

Smoothing (Statistics).

Physical Description:

xxii, 232 pages : illustrations ; 23 cm.

Place of Publication:

Cambridge, U.K. ; New York : Cambridge University Press, 2013.

Summary:

"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."--Cover.

Contents:

1. What are Bayesian filtering and smoothing?

2. Bayesian inference

3. Batch and recursive Bayesian estimation

4. Bayesian filtering equations and exact solutions

5. Extended and unscented Kalman filtering

6. General Gaussian filtering

7. Particle filtering

8. Bayesian smoothing equations and exact solutions

9. Extended and unscented smoothing

10. General Gaussian smoothing

11. Particle smoothing

12. Parameter estimation

13. Epilogue.

Notes:

Includes bibliographical references (pages 219-227) and index.

ISBN:

9781107619289

1107619289

9781107030657

110703065X

OCLC:

840462877

Publisher Number:

40022933761