Recursive identification of HMMs with observations in a finite set

François Le Gland 1 Laurent Mevel 1
1 AS - Signal Processing and Control
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, INRIA Rennes
Abstract : We consider the problem of identification of a partially observed finite-state Markov chain, based on observations in a finite set. We first investigate the asymptotic behaviour of the maximum likelihood estimate (MLE) for the transition probabilities, as the number of observations increases to infinity. In particular, we exhibit the associated contrast function, and discuss consistency issues. Based on this expression, we design a recursive identification algorithm, which converges to the set of local minima of the contrast function.
Type de document :
Communication dans un congrès
Proceedings of the 34th Conference on Decision and Control, New Orleans 1995, Dec 1995, New Orleans, United States. 1, pp.216-221, 1995, 〈10.1109/CDC.1995.478681〉
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https://hal.inria.fr/hal-00912078
Contributeur : Francois Le Gland <>
Soumis le : vendredi 20 décembre 2013 - 18:19:13
Dernière modification le : jeudi 11 janvier 2018 - 06:21:19

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François Le Gland, Laurent Mevel. Recursive identification of HMMs with observations in a finite set. Proceedings of the 34th Conference on Decision and Control, New Orleans 1995, Dec 1995, New Orleans, United States. 1, pp.216-221, 1995, 〈10.1109/CDC.1995.478681〉. 〈hal-00912078〉

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