学院邀请美国佐治亚理工大学 张富民 教授前来我校举行学术讲座。
讲座题目：A Short Course on Discrete Time Dynamic Filtering
Discrete time dynamic filtering algorithms, such as the Kalman filters, the extended Kalman filters, and the particle filters, have found broad applications in engineering disciplines including power systems, robotics, communication systems, etc.
The goal of this short course is to provide an in-depth review of the theoretical foundation underlying these popular discrete time dynamic filtering algorithms. Such understandings will help students and researchers to understand the limitations of the algorithms and to modify these algorithms when necessary. The theoretical foundation will prepare the students to master many advanced variations of the basic algorithms, such as the Rao-Blackwell regularized filter. The course is based on a popular graduate student level course taught by the instructor at the Georgia Institute of Technology.
1. Bayesian Filtering Theory
2. Kalman Filters
3. Extended Kalman Filters
4. Least Mean Square Method and Kalman Filters
5. Random Sampling
6. Particle Filters
7. Rao-Blackwell Filters (if time permits)
Dr. Fumin Zhang is Associate Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He received a PhD degree in 2004 from the University of Maryland (College Park) in Electrical Engineering, and held a postdoctoral position in Princeton University from 2004 to 2007. His research interests include mobile sensor networks, maritime robotics, control systems, and theoretical foundations for cyber-physical systems. He received the NSF CAREER Award in September 2009, the Lockheed Inspirational Young Faculty Award in March 2010, the ONR Young Investigator Program Award in April 2010, and the GT Roger P. Webb Outstanding Junior Faculty Award in April 2011. He is currently serving as the co-chair for the IEEE RAS Technical Committee on Marine Robotics, and the chair for the IEEE CSS Technical Committee on Robotic Control and Manufacturing Automation.