Skip to Main content Skip to Navigation
Conference papers

Particle filters for partially observed Markov chains

Natacha Caylus 1 Arnaud Guyader 2 François Le Gland 1 
1 SIGMA2 - Signal, models, algorithms
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, INRIA Rennes
Abstract : We consider particle filters in a model where the hidden states and the observations form jointly a Markov chain, which means that the hidden states alone do not necessarily form a Markov chain. This model includes as a special case non-linear state-space models with correlated Gaussian noise. Our contribution is to study propagation of errors, stability properties of the filter, and uniform error estimates, using the framework of Le Gland and Oudjane.
Document type :
Conference papers
Complete list of metadata
Contributor : Francois Le Gland Connect in order to contact the contributor
Submitted on : Monday, December 2, 2013 - 12:42:20 AM
Last modification on : Friday, February 4, 2022 - 3:31:24 AM



Natacha Caylus, Arnaud Guyader, François Le Gland. Particle filters for partially observed Markov chains. Proceedings of the IEEE Workshop on Statistical Signal Processing (SSP), Saint―Louis 2003, IEEE--SPS, Sep 2003, Saint―Louis, United States. pp.553-556, ⟨10.1109/SSP.2003.1289524⟩. ⟨hal-00912045⟩



Record views