Lecture on "Backward SDE Methods for Nonlinear Filtering Problems"
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Lecture on "Backward SDE Methods for Nonlinear Filtering Problems"
DateandTime: 2017-05-24 16:36:36

Speaker: Dr.Feng Bao, Assistant Professor, Department of Mathematics, The University of Tennessee at Chattanooga, US

Date: May 24, 2017

Time: 2:30 pm-3:30 pm

Location: 924 Lecture Hall, Block B, Zhixin Building, Central Campus

Sponsor: the School of Mathematics 


Abstract:

We consider a dynamical system modeled by a stochastic differential equation with observational data available for the functional of the system state.  The goal of the nonlinear filtering problem is to find the best estimate of the state of the dynamical system based on the observation. Some well known approaches include extended Kalman filter, particle filter and Zakai filter. In this presentation, we shall present a new nonlinear filtering method, named the backward SDE filter.  The backward SDE filter has the accuracy advantage of continuous filters such as the Zakai filter. In the meantime, it has the same sampling flexibility of discrete filters such as the particle filter.  Both theoretical results and numerical experiments will be presented.


Bio:

Dr.Feng Bao completed his Ph.D. from Auburn University in 2014. He is currently Assistant Professor of Department of Mathematics at The University of Tennessee at Chattanooga. His main research interests include analysis and numerical solution for stochastic differential equations, analysis and numerical solutions for stochastic particle differential equations, uncertainty quantification, data assimilation and inference for stochastic processes, and stochastic optimization. He has published in top journals such as Stochastics and Dynamics, Journal of Computational Physics, Nanotechnology and so on. 


For more information, please visit:

http://www.maths.sdu.edu.cn/backward-sde-methods-for-nonlinear-filtering-problems.html 


Edited by: Shi Yajie




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