Toward Practical N2 Monte Carlo: the Marginal Particle Filter

Toward Practical N2 Monte Carlo: the Marginal Particle Filter

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Sequential Monte Carlo techniques are useful for state estimation in non-linear, non-Gaussian dynamic models. These methods allow us to approximate the joint posterior distribution using sequential importance sampling. In this framework, the dimension of the target distribution grows with each time...

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Detalles Bibliográficos
Main Authors: Klaas, M, de Freitas, N, Doucet, A
Formato: Conference item
Publicado: AUAI Press 2005

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