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Convergence and stability of stochastic theta method for nonlinear stochastic differential equations with piecewise continuous arguments

  • Yuhang Zhang
  • , Minghui Song*
  • , Mingzhu Liu
  • *Corresponding author for this work
  • School of Mathematics, Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

This paper deals with the strong convergence and exponential stability of the stochastic theta (ST) method for stochastic differential equations with piecewise continuous arguments (SDEPCAs) with non-Lipschitzian and non-linear coefficients and mainly includes the following three results: (i) under the local Lipschitz and the monotone conditions, the ST method with θ∈[1/2,1] is strongly convergent to SDEPCAs; (ii) the ST method with θ∈(1/2,1] preserves the exponential mean square stability of SDEPCAs under the monotone condition and some conditions on the step-size; (iii) without any restriction on the step-size, there exists θ∈(1/2,1] such that the ST method with θ∈(θ,1] is exponentially stable in mean square. Moreover, for sufficiently small step-size, the rate constant can be reproduced. Some numerical simulations are provided to illustrate the theoretical results.

Original languageEnglish
Article number113849
JournalJournal of Computational and Applied Mathematics
Volume403
DOIs
StatePublished - 15 Mar 2022
Externally publishedYes

Keywords

  • Convergence of the ST method
  • Exponential mean square stability
  • Stochastic differential equations with piecewise continuous arguments
  • Super-linear growth
  • The stochastic theta (ST) method

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