Nonlinear filtering with continuous time perfect observations and noninformative quadratic variation

Marc Joannides 1 François Le Gland 1
1 SIGMA2 - Signal, models, algorithms
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, INRIA Rennes
Abstract : We consider the problem of estimating the state of a diffusion process, based on continuous time observations in singular noise. As long as the observations are regular values of the observation function, we derive an equation for the density (w.r.t. the canonical Lebesgue measure on the corresponding level set) of the conditional probability distribution of the state, given the past observations. The proof is based on the idea of decomposition of solutions of SDE, as introduced by Kunita (1981)
Type de document :
Communication dans un congrès
Proceedings of the 36th Conference on Decision and Control, San Diego 1997, Dec 1997, San Diego, United States. 2, pp.1645-1650, 1997, 〈10.1109/CDC.1997.657750〉
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https://hal.inria.fr/hal-00912058
Contributeur : Francois Le Gland <>
Soumis le : lundi 2 décembre 2013 - 00:53:56
Dernière modification le : jeudi 11 janvier 2018 - 06:20:10

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Marc Joannides, François Le Gland. Nonlinear filtering with continuous time perfect observations and noninformative quadratic variation. Proceedings of the 36th Conference on Decision and Control, San Diego 1997, Dec 1997, San Diego, United States. 2, pp.1645-1650, 1997, 〈10.1109/CDC.1997.657750〉. 〈hal-00912058〉

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