A Kalman filter primer /
Eubank (mathematics and statistics, Arizona State U.) offers a self-contained, concise rigorous derivation of all the basic Kalman filter recursions from first principles. He lays out the basic prediction problem for signal-plus-noise models, deriving the Gramm-Schmidt algorithm and Cholesky decompo...
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| Format: | eBook |
| Language: | English |
| Language Notes: | English. |
| Published: |
Boca Raton, Fla. :
Chapman & Hall/CRC,
2006.
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| Series: | Statistics, textbooks and monographs ;
v. 186. |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | Eubank (mathematics and statistics, Arizona State U.) offers a self-contained, concise rigorous derivation of all the basic Kalman filter recursions from first principles. He lays out the basic prediction problem for signal-plus-noise models, deriving the Gramm-Schmidt algorithm and Cholesky decomposition. He covers the fundamental covariance struc. |
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| Item Description: | Description based upon print version of record. |
| Physical Description: | 1 online resource (199 p.). |
| Bibliography: | Includes bibliographical references (p. 183-184) and index. |
| ISBN: | 0429117590 9780429117596 1281326178 9781281326171 9786611326173 6611326170 1420028677 9781420028676 |