Title :
Recursive identification for semiparametric multi-channel wiener systems
Author_Institution :
Sch. of Math. Sci., Dalian Univ. of Technol., Dalian, China
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;
Conference_Titel :
Control Conference (CCC), 2014 33rd Chinese
Conference_Location :
Nanjing
DOI :
10.1109/ChiCC.2014.6896117
