题目：Stochastic Averaging 

摘要：

I will present the Khasminskii method of stochastic averaging [1] for the case when the unperturbed system is non-random (and finite-dimensional). The presentation is simplified compare to [1] due to new technical solutions, found to work with stochastic averaging for PDEs (see [2] for some of them in the case of DETERMINISTIC perturbations). At the end of the course I will discuss what changes if the unperturbed system is stochastic.

参考文献：

[1] Khasminski R., On the avaraging principle for Ito stochastic differential equations (in Russ.), Kybernetika 4 (1968), 260-279.

[2] Jian W., Kuksin S.B., Wu Y., Krylov--Bogolyubov averaging, Russian Mathematical Surveys, 75:3 (2020)

第四次

时间：2020/11/17 16:00-18:00

腾讯会议地址： https://meeting.tencent.com/s/QvzZbmSbZnyE

会议ID：412 222 166 

第五次

时间：2020/11/24 16:00-18:00

腾讯会议地址： https://meeting.tencent.com/s/T4clhPGaZitG

会议ID：413 249 314 

第六次

时间：2020/12/1 16:00-18:00

腾讯会议地址：https://meeting.tencent.com/s/CQ2eKTgjvaiX

会议ID：116 855 675