DocumentCode
232634
Title
Recursive identification for semiparametric multi-channel wiener systems
Author
Xing-Min Chen
Author_Institution
Sch. of Math. Sci., Dalian Univ. of Technol., Dalian, China
fYear
2014
fDate
28-30 July 2014
Firstpage
6786
Lastpage
6791
Abstract
Recursive identification for semiparametric multi-channel Wiener systems is considered in the paper. Based on stochastic approximation, the recursive estimates are given for coefficients of each linear subsystem and the weighed coefficient with the help of the average derivative approach, then recursive nonparametric estimate is derived for the system nonlinearity by using kernel method. All estimates are recursive and are proved to be strongly consistent under reasonable conditions.
Keywords
MIMO systems; approximation theory; nonlinear systems; parameter estimation; stochastic processes; MIMO Wiener systems; average derivative approach; kernel method; linear subsystem; recursive identification; recursive nonparametric estimate; semiparametric multichannel Wiener systems; stochastic approximation; system nonlinearity; weighed coefficient; Additives; Approximation methods; Estimation; Kernel; MIMO; Noise; Stochastic processes; Kernel Estimation; Multi-Channel Wiener System; Recursive Identification; Semiparametric Estimation; Stochastic Approximation;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2014 33rd Chinese
Conference_Location
Nanjing
Type
conf
DOI
10.1109/ChiCC.2014.6896117
Filename
6896117
Link To Document