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Online Expectation-Maximization type algorithms for parameter estimation in general state space models

Abstract:
In this paper we present new online algorithms to estimate static parameters in nonlinear non Gaussian state space models. These algorithms rely on online Expectation-Maximization (EM) type algorithms. Contrary to standard Sequential Monte Carlo (SMC) methods recently proposed in the literature, these algorithms do not degenerate over time.

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Journal:
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume:
6
Pages:
69-72
Publication date:
2003-01-01
ISSN:
1520-6149
URN:
uuid:0f78343e-1e2e-47f7-8196-f004b5d53fe3
Source identifiers:
190643
Local pid:
pubs:190643
Language:
English

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