Looking for an examination copy?
If you are interested in the title for your course we can consider offering an examination copy. To register your interest please contact firstname.lastname@example.org providing details of the course you are teaching.
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/GNU Octave source code is available for download at www.cambridge.org/sarkka, promoting hands-on work with the methods.Read more
- The first book to draw together estimation, smoothing and Monte Carlo methods
- Examples and exercises demonstrate practical use of the algorithms
- Matlab code is available for download, allowing readers hands-on work with the methods
13th Apr 2017 by Wanghs
this is a very professional book about Bayesian filtering and Smoothing .
Review was not posted due to profanity×
- Date Published: October 2013
- format: Hardback
- isbn: 9781107030657
- length: 254 pages
- dimensions: 234 x 157 x 17 mm
- weight: 0.54kg
- contains: 55 b/w illus. 60 exercises
- availability: Available
Table of Contents
Symbols and abbreviations
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
Appendix: additional material
Welcome to the resources site
Here you will find free-of-charge online materials to accompany this book. The range of materials we provide across our academic and higher education titles are an integral part of the book package whether you are a student, instructor, researcher or professional.
Find resources associated with this titleYour search for '' returned .
Type Name Unlocked * Format Size
*This title has one or more locked files and access is given only to instructors adopting the textbook for their class. We need to enforce this strictly so that solutions are not made available to students. To gain access to locked resources you either need first to sign in or register for an account.
These resources are provided free of charge by Cambridge University Press with permission of the author of the corresponding work, but are subject to copyright. You are permitted to view, print and download these resources for your own personal use only, provided any copyright lines on the resources are not removed or altered in any way. Any other use, including but not limited to distribution of the resources in modified form, or via electronic or other media, is strictly prohibited unless you have permission from the author of the corresponding work and provided you give appropriate acknowledgement of the source.
If you are having problems accessing these resources please email email@example.com
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email firstname.lastname@example.orgRegister Sign in
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.Continue ×