时 间：2023年5月29日（周一）9：00
地 点：ZOOM会议：88585192220 会议密码：113811
题 目：非线性滤波算法——深度学习方法(Computational Nonlinear Filtering: A Deep Learning Approach)
报告人：殷刚 美国康涅狄格大学教授
主持人：钱林义 教授
主 办：经管学部、华东师范大学中国经济研究中心
摘 要：
Nonlinear filtering is a fundamental problem in information theory, communication, signal processing, control and optimization, and systems theory. In the 1960s, celebrated results on nonlinear filtering were obtained. Nevertheless, the computational issues for nonlinear filtering remained to be a long-standing and challenging problem. In this talk, in lieu of treating an infinite dimensional problem for obtaining the conditional distribution, or conditional measure, we construct finite-dimensional approximations using deep neural networks for the optimal weights. Two recursions are used in the algorithm. One of them is the approximation of the optimal weight and the other is for approximating the optimal learning rate. [This is a joint work with Qing Zhang (University of Georgia), and Hongjiang Qian (University of Connecticut).]
报告人简介：
殷刚，美国康涅狄格大学教授，担任国际电气和电子工程师协会（IEEE）、国际自动控制联合会(IFAC)、美国工业与应用数学学会（SIAM）会士等多个国际著名学会会士；
现任《SIAM Journal on Control and Optimization》主编，《Applied Mathematics and Optimization》和《ESAIM: Control, Optimisation and Calculus of Variations》副主编，并担任其他多个期刊的编辑委员会成员；
研究兴趣包括随机过程、随机系统理论和应用