Particle filtering for partially observed Gaussian state space models

Particle filtering for partially observed Gaussian state space models

Solving Bayesian estimation problems where the posterior distribution evolves over time through the accumulation of data has many applications for dynamic models. A large number of algorithms based on particle filtering methods, also known as sequential Monte Carlo algorithms, have recently been pro...

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Dades bibliogràfiques
Autors principals:	Andrieu, C, Doucet, A
Format:	Journal article
Idioma:	English
Publicat:	2002

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