Distributed filtering in sensor networks with imperfect communication

发布者:系统管理员发布时间:2013-05-17浏览次数:1781

报告题目: Distributed filtering in sensor networks with imperfect communication
报 告 人: Daniel Ho 教授
  香港城市大学
报告时间: 5月24日(周五)下午2:00-3:00
报告地点: 九龙湖数学系第一报告厅
相关介绍:
A sensor network consists of spatially distributed sensors to monitor physical or environmental conditions, and to cooperatively communicate their data through the network. Due to the unavoidable noise during data transmission, filtering design is a fundamental problem in sensor networks. In this presentation, the H distributed filtering in sensor networks with imperfect communication will be introduced. In our work, different kinds of communication constraints have been considered: i) partial information transmission; ii) sampling data; iii) data packet dropout. These constraints would lead to that less information of sensors can be received, which makes the distributed filtering problem much harder to be solved.
Prof. Daniel W. C. Ho received a first class BSc, MSc and PhD degrees in mathematics from the University of Salford (UK) in 1980, 1982 and 1986 respectively. From 1985 to 1988, he was a Research Fellow in Industrial Control Unit, University of Strathclyde (Glasgow, Scotland). In 1989, he joined the Department of Mathematics, City University of Hong Kong. Prof. Ho is Associate Editor of Asian Journal of ControlJournal of Franklin Institute,International Journal of Automation and Computing and a member of Editorial board of IET Control Theory & ApplicationsSystems Science and Control Engineering (An Open Access Journal), Dynamics of Continuous, Discrete and Impulsive Systems: Series B (Applications & Algorithm). Professor Ho is a Guest Professor of East China University of Science and Technology (2011-2014), Shanghai, China, and Chang Jiang Chair Professor, Nanjing University of Science and Technology, China. (2012-2015) awarded by Ministry of Education, China. He is also a senior member of IEEE. His research interests include control theory, estimation and filtering theory, complex dynamical distributed networks, multi-agent networks, nonlinear singular systems and stochastic systems.