Conference item
Particle filter as a controlled Markov chain for on-line parameter estimation in general state space models
- Abstract:
- In this paper we present a novel optimization method for on-line maximum likelihood estimation (MLE) of the static parameters of a general state space model. Our approach is based on viewing the particle filter as a controlled Markov chain, where the control is the unknown static parameters to be identified, The algorithm relies on the computation of the gradient of the particle filter using a score function approach. © 2006 IEEE.
- Publication status:
- Published
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Bibliographic Details
- Volume:
- 3
- Pages:
- 329-+
- Host title:
- 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol III, Proceedings
- Publication date:
- 2006-01-01
- ISSN:
-
1520-6149
- Source identifiers:
-
172716
- ISBN-10:
- 142440469X
- ISBN-13:
- 9781424404698
Item Description
- Keywords:
- Pubs id:
-
pubs:172716
- UUID:
-
uuid:61551d0b-d3b7-46d3-8ffc-00719159aef8
- Local pid:
- pubs:172716
- Deposit date:
- 2012-12-19
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- Copyright date:
- 2006
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