14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper WeA4.3

Wang, Le Yi (Wayne State Univ.), Yin, George (Wayne State Univ.), Zhang, Ji-Feng (Chinese Acad. of Sciences)

System Identification Using Quantized Data

Scheduled for presentation during the Regular Session "Identification for Control" (WeA4), Wednesday, March 29, 2006, 11:10−11:30, Cummings Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 17, 2018

Keywords Identification for Control, Recursive Identification


System identification of plants using set-valued output observations is investigated under a stochastic framework for understanding relationships between identification space and time complexities. While this problem exists inherently in all systems whose outputs must be digitized by sampling and quantization, it is especially relevant to system identification problems in which data-flow rates are limited due to computer networking, communications, wireless channels, etc. Empirical measures are of fundamental utility in deriving identification algorithms in such problems. Asymptotic properties of empirical measures yield a general result for asymptotic analysis of space and time complexities. This result leads to a principle of asymptotic separation of space and time complexities, that is employed to solve the problems of robust, optimal, and adaptive selections of sensor thresholds. Insights gained from these understandings provide a feasible approach for optimal utility of communication bandwidth resources in enhancing identification accuracy.