Toward Practical N2 Monte Carlo: the Marginal Particle Filter

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...

Повний опис

Бібліографічні деталі
Автори:	Klaas, M, de Freitas, N, Doucet, A
Формат:	Conference item
Опубліковано:	AUAI Press 2005

Toward practical N2 Monte Carlo: The Marginal Particle Filter за авторством Klaas, M, De Freitas, N, Doucet, A

Опубліковано 2005

Journal article

Toward Practical N2 Monte Carlo: the Marginal Particle Filter

Toward practical N2 Monte Carlo: The Marginal Particle Filter за авторством Klaas, M, De Freitas, N, Doucet, A

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