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Stochastic semi-discretization for linear stochastic delay differential equations

Stochastic semi-discretization for linear stochastic delay differential equations
Stochastic semi-discretization for linear stochastic delay differential equations
An efficient numerical method is presented to analyze the moment stability and stationary behavior of linear stochastic delay differential equations. The method is based on a special kind of discretization technique with respect to the past effects. The resulting approximate system is a high dimensional linear discrete stochastic mapping. The convergence properties of the method is demonstrated with the help of the stochastic Hayes equation and the stochastic delayed oscillator.
0029-5981
879-898
Sykora, Henrik
e89d4c51-f8bc-4258-a9cc-38f249270757
Bachrathy, Daniel
4834c669-68f1-4e08-b5e4-5ce5abe30bc4
Stepan, Gabor
5392004a-eed4-41eb-a137-b7586e8b54a9
Sykora, Henrik
e89d4c51-f8bc-4258-a9cc-38f249270757
Bachrathy, Daniel
4834c669-68f1-4e08-b5e4-5ce5abe30bc4
Stepan, Gabor
5392004a-eed4-41eb-a137-b7586e8b54a9

Sykora, Henrik, Bachrathy, Daniel and Stepan, Gabor (2019) Stochastic semi-discretization for linear stochastic delay differential equations. International Journal for Numerical Methods in Engineering, 119 (9), 879-898. (doi:10.1002/nme.6076).

Record type: Article

Abstract

An efficient numerical method is presented to analyze the moment stability and stationary behavior of linear stochastic delay differential equations. The method is based on a special kind of discretization technique with respect to the past effects. The resulting approximate system is a high dimensional linear discrete stochastic mapping. The convergence properties of the method is demonstrated with the help of the stochastic Hayes equation and the stochastic delayed oscillator.

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e-pub ahead of print date: 8 April 2019
Published date: 31 August 2019

Identifiers

Local EPrints ID: 471911
URI: http://eprints.soton.ac.uk/id/eprint/471911
ISSN: 0029-5981
PURE UUID: 41e49c64-3f33-475f-a87a-8ba70951c0de

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Date deposited: 22 Nov 2022 17:44
Last modified: 16 Mar 2024 22:24

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Contributors

Author: Henrik Sykora
Author: Daniel Bachrathy
Author: Gabor Stepan

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