Bayesian Filtering and Smoothing (Record no. 589)
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000 -LEADER | |
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fixed length control field | 01604nam a2200169Ia 4500 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | OSt |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20230511114151.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 170804s2013 xx 000 0 und d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9781107619289 |
100 ## - MAIN ENTRY--PERSONAL NAME | |
Personal name | Simo Särkkä (Sarkka) |
245 ## - TITLE STATEMENT | |
Title | Bayesian Filtering and Smoothing |
260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
Name of publisher, distributor, etc. | Cambridge University Press |
Date of publication, distribution, etc. | 2013 |
Place of publication, distribution, etc. | Cambridge, U.K. |
300 ## - Physical Description | |
Pages: | 252 p, |
490 ## - SERIES STATEMENT | |
Series statement | Part of Institute of Mathematical Statistics Textbooks |
520 ## - SUMMARY, ETC. | |
Summary, etc. | 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. |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Source of classification or shelving scheme | |
Koha item type | Book |
Withdrawn status | Lost status | Damaged status | Not for loan | Collection code | Home library | Shelving location | Date acquired | Full call number | Accession No. | Koha item type |
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ICTS | Rack No 5 | 12/22/2016 | QA279.5 | 00589 | Book |