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Jialin Hong--Fundamental Convergence of Numerical Methods for Stochastic Differential Equations
发布人:管理员LIU  发布时间:2016-07-20   浏览次数:494


Abstract: In this talk we review theoretical results on the mean-square convergence of numerical methods for stochastic ordinary differential equations, stochastic delay differential equations, neutral stochastic delay differential equations, jump-diffusion differential equations, neutral stochastic delay differential equations with jump-diffusion, stochastic partial differential equations. These results are called fundamental convergence theorems of numerical methods for stochastic differential equations. In this talk we propose a fundamental convergence theorem of semidiscretisation for stochastic Schroedinger equations in temporal direction. And based on Feynman-Kac type formula on backward stochastic differential equations, we present a fundamental convergence theorem of numerical methods for backward stochastic differential equations, and apply it to the mean-square convergence of numerical schemes for backward stochastic differential equations.


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