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Backward SDE method for nonlinear filtering problems
澳门新葡8455最新网站:2016年12月26日 15:30 点击数:

报告人:曹延昭

报告地点:澳门新葡8455最新网站二楼会议室

报告澳门新葡8455最新网站:2016年12月27日星期二15:00-16:00

邀请人:

报告摘要:

A nonlinear filtering problem can be classified as a stochastic Bayesian optimization problem of identifying the state of a stochastic dynamical system based on noisy observations of the system. Well known numerical simulation methods include unscented Kalman filters and particle filters. In this talk, we consider a class of efficient numerical methods based on forward backward stochastic differential equations. The backward SDEs for nonlinear filtering problems are similar to the Fokker-Planck equations for stochastic differential equations(SDEs). We will describe the process of deriving such backward SDEs as well as high order numerical algorithms to solve them, which in turn solve nonlinear filtering problems.

主讲人概况:

曹延昭,美国Auburn University数学系教授,主要从事非线性微分方程数值解的研究。现任美国《SIAM J. Numerical Analysis》等国际杂志编委。

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