Plenary Lecture

System Identification with Quantized Observations

Prof. Le Yi Wang
Department of Electrical and Computer Engineering
Wayne State University
Detroit, Michigan 48202
USA
Email: lywang@indigo.eng.wayne.edu

Abstract: Binary-valued or quantized sensors are employed in many practical systems. Typical examples include switching sensors for exhaust gas oxygen, traffic condition indicators in the ATM (asynchronous transmission mode), neural networks. More important, the new paradigm of sensor networks, networked systems and control, e-health systems for remote monitoring, diagnosis, etc. mandate that signals must be sent over a communication network, and hence must be quantized. In other words, pursuing modeling and control of systems that involve communication channels will need, as a foundation, identification and complexity analysis of system identification with quantized observations.
In this talk, recent advances will be presented on system identification with binary or quantized observations. We will start with the fundamental aspects of identification algorithms, strong convergence, convergence rates, and algorithm efficiency (optimality). Findings from these fundamental issues are then employed to understand such identification problems in various system and environment settings, including different system models (gain, finite impulse response, and rational systems), joint identification of systems and noise distributions, impact of communication channels on identification accuracy and speed, selection of quantization thresholds, etc.

Brief Biography of the Speaker:
Le Yi Wang received the Ph.D. degree in electrical engineering from McGill University, Montreal, Canada, in 1990. Since 1990, he has been with Wayne State University, Detroit, Michigan, where he is currently a Professor in the Department of Electrical and Computer Engineering. His research interests are in the areas of complexity and information, system identification, robust control, H-infinity optimization, time-varying systems, adaptive systems, hybrid and nonlinear systems, information processing and learning, as well as medical, automotive, communications, and computer applications of control methodologies.
Dr. Wang was awarded the Research Initiation Award in 1992 from the National Science Foundation. He also received the Faculty Research Award from Wayne State University, in 1992, and the College Outstanding Teaching Award from the College of Engineering, Wayne State University, in 1995. He was a keynote speaker in three international conferences. He serves on the IFAC Technical Committee on Modeling, Identification and Signal Processing. He served as an Associate Editor of the IEEE Transactions on Automatic Control, and currently is an Editor of the Journal of System Sciences and Complexity, an Associate Editor of Journal of Control Theory and Applications, an Associate Editor of International Journal of Control and Intelligent Systems.