Efficient Sequential Monte Carlo Using Interpolation
dc.contributor.author | Hover, Franz S. | |
dc.date.accessioned | 2010-03-08T22:05:49Z | |
dc.date.available | 2010-03-08T22:05:49Z | |
dc.date.issued | 2010-03-08T22:05:49Z | |
dc.identifier.uri | http://hdl.handle.net/1721.1/52403 | |
dc.description.abstract | A 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.iso | en_US | en |
dc.title | Efficient Sequential Monte Carlo Using Interpolation | en |
dc.type | Article | en |