Русская версия
ISSN 1817-2172, рег. Эл. № ФС77-39410, ВАК

Differential Equations and Control Processes
(Differencialnie Uravnenia i Protsesy Upravlenia)

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Statistical Prediction Algorithms for Nonlinear Stochastic Jump-diffusion Systems

Author(s):

Tatyana Averina

Institute of Computational Mathematics and Mathematical Geophysics SB RAS
Novosibirsk state university, Computational mathematics department

ata@osmf.sscc.ru

Konstantin A. Rybakov

Moscow aviation institute (national research university),
Mathematical cybernetics department, associate professor
associate professor, candidate of physico-mathematical sciences

rkoffice@mail.ru

Abstract:

In this paper we discuss an evolution of the new approach to the prediction problem for nonlinear stochastic differential systems with a Poisson component. The proposed approach is based on reducing the prediction problem to the analysis of stochastic jump-diffusion systems with terminating and branching paths. The solution of analysis problem can be found approximately by using numerical methods for solving stochastic differential equations and methods for modeling inhomogeneous Poisson flows.

Keywords

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