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...

書誌詳細
主要な著者:	Klaas, M, de Freitas, N, Doucet, A
フォーマット:	Conference item
出版事項:	AUAI Press 2005

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