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On Persistence of Convergence of Kernel Density Estimates in Particle Filtering

Publikace na Matematicko-fyzikální fakulta |
2020

Tento text není v aktuálním jazyce dostupný. Zobrazuje se verze "en".Abstrakt

A sufficient condition is provided for keeping the character of the filtering density in the filtering task. This is done for the Sobolev class of filtering densities.

As a consequence, estimating the filtering density in particle filtering persists its convergence at any time of filtering. Specifying the condition complements previous results on using the kernel density estimates in particle filtering.