Simo Sarkka (Finland Aalto University), Lennart Svensson (Gothenberg Chalmers University of Technology)

Bayesian Filtering and Smoothing

• Broschiertes Buch

Produktbeschreibung

The second edition of this accessible introduction for graduate students and advanced undergraduates presents the current state-of-the-art filtering and smoothing methods in a unified Bayesian framework. The book introduces all the main concepts and ideas, and contains numerous examples and exercises to let you put the theory into practice.

Produktdetails

• Institute of Mathematical Statistics Textbooks
• Verlag: Cambridge University Press
• 2 Revised edition
• Seitenzahl: 430
• Erscheinungstermin: 15. Juni 2023
• Englisch
• Abmessung: 224mm x 152mm x 27mm
• Gewicht: 640g
• ISBN-13: 9781108926645
• ISBN-10: 1108926649
• Artikelnr.: 67129184

Autorenporträt

Simo Särkkä is Associate Professor in the Department of Electrical Engineering and Automation at Aalto University, Finland. His research interests center on state estimation and stochastic modeling, and he has authored two books (2013 and 2019) on these topics. He is Fellow of ELLIS, Senior Member of IEEE, a recipient of multiple paper awards, and he has been Chair of MLSP and FUSION conferences.

Inhaltsangabe

Symbols and abbreviations
1. What are Bayesian filtering and smoothing?
2. Bayesian inference
3. Batch and recursive Bayesian estimation
4. Discretization of continuous-time dynamic models
5. Modeling with state space models
6. Bayesian filtering equations and exact solutions
7. Extended Kalman filtering
8. General Gaussian filtering
9. Gaussian filtering by enabling approximations
10. Posterior linearization filtering
11. Particle filtering
12. Bayesian smoothing equations and exact solutions
13. Extended Rauch-Tung-Striebel smoothing
14. General Gaussian smoothing
15. Particle smoothing
16. Parameter estimation
17. Epilogue
Appendix. Additional material
References
Index.