Title: Monte-Carlo methods in nonlinear filtering and importance sampling
Abstract:For the calculation of conditional expectations in nonlinear filtering of Markov processes, one may think to use Monte-Carlo techniques, as an alternative to the numerical solution of Zakai equation (...For the calculation of conditional expectations in nonlinear filtering of Markov processes, one may think to use Monte-Carlo techniques, as an alternative to the numerical solution of Zakai equation (a stochastic PDE). We show that a direct implementation of this idea is unefficient, and we propose a modified algorithm, that uses importance sampling, where our choice of the new probability is based on large deviations arguments.Read More
Publication Year: 1984
Publication Date: 1984-12-01
Language: en
Type: preprint
Indexed In: ['crossref']
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Cited By Count: 2
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