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Title An introduction to Kalman filtering with MATLAB examples / Narayan Kovvali, Mahesh Banavar, and Andreas Spanias.

Location Call No. Status Notes
 Libraries Electronic Books  ELECTRONIC BOOK-Ebook Central    AVAIL. ONLINE
Description 1 online resource.
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Series Synthesis lectures on signal processing ; #12. 1932-1236
Reproduction Electronic reproduction. Perth, W.A. Available via World Wide Web.
Note Online resource; title from PDF title page (Morgan & Claypool, viewed on October 16, 2013).
Bibliography Includes bibliographical references (pages 67-70).
Contents 1. Introduction.
2. The estimation problem -- 2.1 Background -- 2.1.1 Example: maximum-likelihood estimation in Gaussian noise -- 2.2 Linear estimation -- 2.3 The Bayesian approach to parameter estimation -- 2.3.1 Example: estimating the bias of a coin -- 2.4 Sequential Bayesian estimation -- 2.4.1 Example: the 1-D Kalman filter.
3. The Kalman filter -- 3.1 Theory -- 3.2 Implementation -- 3.2.1 Sample MATLAB code -- 3.2.2 Computational issues -- 3.3 Examples -- 3.3.1 Target tracking with radar -- 3.3.2 Channel estimation in communications systems -- 3.3.3 Recursive least squares (RLS) adaptive filtering.
4. Extended and decentralized Kalman filtering -- 4.1 Extended Kalman filter -- 4.1.1 Example: predator-prey system -- 4.2 Decentralized Kalman filtering -- 4.2.1 Example: distributed object tracking.
5. Conclusion -- Notation -- Bibliography -- Authors' biographies.
Indexed In: Compendex
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Subject MATLAB.
Kalman filtering.
dynamical system
parameter estimation
tracking
state space model
sequential
Bayesian estimation
linearity
Gaussian noise
Kalman filter
Added Author Banavar, Mahesh K., author.
Spanias, Andreas, author.
Ebooks Corporation
Related To Print version: 9781627051392
ISBN 9781627051408 (electronic bk.)
1627051406 (electronic bk.)
1627051392
9781627051392
9781627051392 (pbk.)
UPC # 10.2200/S00534ED1V01Y201309SPR012 doi
OCLC # EBC1495851
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