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                Numerical Methods for Stochastic Differential Equations: part II

                發布者:文明辦作者:發布時間:2021-07-14瀏覽次數:10


                主講人:Professor Xuerong Mao,University of Strathclyde


                時間:2021年7月18日19:00


                地點:騰訊會議 737 3753 2094


                舉辦單位:數理學院


                主講人介紹:英國思克萊德大學(University of Strathclyde)教授,愛丁堡皇家學會(即蘇格蘭皇家學院)院士。2015年度英國Leverhulme 研究獎,2016 年度英國皇家協會Wolfson 研究功勛獎。


                內容介紹:Up to 2002, all positive results on the numerical methods for SDEs were based on  a much more restrictive global Lipschitz assumption (namely both shift and  diffusion coefficients satisfy the global Lipschitz condition). However, the  global Lipschitz assumption rules out most realistic models. In 2002, Higham,  D.J., Mao, X. and Stuart, A.M. (SIAM Journal on Numerical Analysis 40(3) (2002),  1041-1063) were first to study the strong convergence of numerical solutions of  SDEs under a local Lipschitz condition. The field of numerical analysis of SDEs  now has a very active research profile, much of which builds on the techniques  developed in that paper, which has so far attracted 653 Google Scholar  Citations. In particular, the theory developed there has formed the foundation  for several recent very popular methods, including tamed Euler-Maruyama method  and truncated Euler-Maruyama. This summer SDE course will begin with Higham et  al 2002 but concentrate on the truncated Euler-Maruyama. The course will not  only discuss the finite-time strong convergence and its rates but also the  long-term properties including stability and boundedness. As an important  application, the course will develop new numercial schemes for the well-known  stochastic Lotka--Volterra model for interacting multi-species. We will show how  to modify the truncated Euler-Maruyama to establish a new positive preserving  truncated EM (PPTEM).