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dc.contributor.authorHover, Franz S.
dc.date.accessioned2010-03-08T22:05:49Z
dc.date.available2010-03-08T22:05:49Z
dc.date.issued2010-03-08T22:05:49Z
dc.identifier.urihttp://hdl.handle.net/1721.1/52403
dc.description.abstractA limitation common to all sequential Monte Carlo algorithms is the computational demand of accurately describing an arbitrary distribution, which may preclude real-time implementation for some systems. We propose using interpolation to construct a high accuracy approximation to the importance density. The surrogate density can then be efficiently evaluated in place of sampling the true importance density, allowing for the propagation of a large number of particles at reduced cost. Numerical examples are given demonstrating the utility of the approach.en
dc.language.isoen_USen
dc.titleEfficient Sequential Monte Carlo Using Interpolationen
dc.typeArticleen


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