Title :
Is Wiener/Hammerstein system identification really nonlinear?
Author :
Cai, Zhijun ; Bai, Er-Wei
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Iowa, Iowa City, IA, USA
Abstract :
Currently, a number of methods exist for identifying nonlinear Wiener and Hammerstein systems. However, there is no attempt to address the fundamental questions of how nonlinear these identifications really are and why the existing methods work? In this paper, we try to answer the questions by investigating the objective function used to identify those systems. The results show that for both Hammerstein and Wiener identifications, the cost function is globally monotone has one and only one minimum.
Keywords :
identification; nonlinear systems; Wiener/Hammerstein system identification; nonlinear Hammerstein system; nonlinear Wiener system; objective function; Cost function; Finite impulse response filter; Matrix decomposition; Noise; Polynomials; Simulation; USA Councils;
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-7745-6
DOI :
10.1109/CDC.2010.5717703