Optimal ϑ -Methods for Mean-Square Dissipative Stochastic Differential Equations
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 12949 LNCS, Page: 121-134
2021
- 2Citations
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- Citations2
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Conference Paper Description
In this paper, we address our investigation to the numerical integration of nonlinear stochastic differential equations exhibiting a mean-square contractive character along the exact dynamics. We specifically focus on the conservation of this qualitative feature along the discretized dynamics originated by applying stochastic ϑ -methods. Retaining the mean-square contractivity under time discretization is translated into a proper stepsize restriction. Here we analyze the choice of the optimal parameter ϑ making this restriction less demanding and, at the same time, maximizing the stability interval. A numerical evidence is provided to confirm our theoretical results.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85115359037&origin=inward; http://dx.doi.org/10.1007/978-3-030-86653-2_9; https://link.springer.com/10.1007/978-3-030-86653-2_9; https://dx.doi.org/10.1007/978-3-030-86653-2_9; https://link.springer.com/chapter/10.1007/978-3-030-86653-2_9
Springer Science and Business Media LLC
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