Numerical Algorithms · 2017 · 53 citations · 15 references
EngineeringComputational EngineeringDifferential EquationsStochastic ModelingStochastic ProcessesConvergence AnalysisNumerical AlgorithmsNumerical ConvergenceNumerical Methods For Differential EquationsStochastic CalculusStochastic Differential EquationsConvergenceDelay EquationsNumerical Methods For Stochastic Differential Equations
The numerical solutions of stochastic differential delay equations (SDDEs) under the generalized Khasminskii-type condition were discussed by Mao (Appl. Math. Comput. 217, 5512–5524 2011), and the theory there showed that the Euler–Maruyama (EM) numerical solutions converge to the true solutions in probability. However, there is so far no result on the strong convergence (namely in L p ) of the numerical solutions for the SDDEs under this generalized condition. In this paper, we will use the truncated EM method developed by Mao (J. Comput. Appl. Math. 290, 370–384 2015) to study the strong convergence of the numerical solutions for the SDDEs under the generalized Khasminskii-type condition.
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