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01269nam a2200217 a 4500 |
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553786 |
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20171111230018.0 |
| 008 |
080721s2009 nyuab b 001 0 eng |
| 020 |
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|a 9780470180945 (hbk.)
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| 040 |
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|a DLC
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| 050 |
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|a TK5102.9
|b .C3187 2009
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| 082 |
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|2 22
|a 621.382/2
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| 100 |
1 |
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|a Candy, J. V.
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| 245 |
1 |
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|a Bayesian signal processing :
|b classical, modern, and particle filtering methods /
|c James V. Candy.
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| 260 |
1 |
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|a Hoboken, N.J. :
|b Wiley :
|c c2009.
|b IEEE,
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| 300 |
1 |
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|a xxiii, 445 p. :
|b ill., map ;
|c 25 cm.
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| 504 |
1 |
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|a Includes bibliographical references and index.
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| 505 |
1 |
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|a 1. Introduction -- 2. Bayesian estimation -- 3. Simulation-based Bayesian methods -- 4. State-space models for Bayesian processing -- 5. Classical Bayesian state-space processors -- 6. Modern Bayesian state-space processors -- 7. Particle-based Bayesian state-space processors -- 8. Joint Bayesian state/parametric processors -- 9. Discrete hidden Markov model Bayesian processors -- 10. Bayesian processors for physics-based applications -- Appendix A. Probability & statistics overview.
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| 650 |
1 |
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|a Signal processing
|x Mathematics
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| 650 |
1 |
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|a Bayesian statistical decision theory
|
| 952 |
|
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|a GrThPMO
|b 59b016316c5ad17d7e5ada8a
|c 952a
|d 9528
|e TK5102.9.C3187 2009
|t 7
|x m
|z Books
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