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Sequential Monte Carlo smoothing for general state space hidden Markov models
ANNALS OF APPLIED PROBABILITY, no. 6 (2011): 2109-2145
摘要
Computing smoothing distributions, the distributions of one or more states conditional on past, present, and future observations is a recurring problem when operating on general hidden Markov models. The aim of this paper is to provide a foundation of particle-based approximation of such distributions and to analyze, in a common unifying ...更多
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