Using maximum cross section method for filtering jump-diffusion random processes

Tatyana A. Averina; Konstantin A. Rybakov

doi:10.1515/rnam-2020-0005

Using maximum cross section method for filtering jump-diffusion random processes

Tatyana A. Averina, Konstantin A. Rybakov

Computational Mathematics Section

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

The paper is focused on problem of filtering random processes in dynamical systems whose mathematical models are described by stochastic differential equations with a Poisson component. The solution of a filtering problem supposes simulation of trajectories of solutions to a stochastic differential equation. The trajectory modelling procedure includes simulation of a Poisson flow permitting application of the maximum cross section method and its modification.

Original language	English
Pages (from-to)	55-67
Number of pages	13
Journal	Russian Journal of Numerical Analysis and Mathematical Modelling
Volume	35
Issue number	2
DOIs	https://doi.org/10.1515/rnam-2020-0005
Publication status	Published - 1 Apr 2020

Keywords

estimation
filtering
maximum cross section method
particle filter
particle method
statistical modelling
Stochastic differential equation with jumps

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Using maximum cross section method for filtering jump-diffusion random processes

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