DocumentCode
442224
Title
Nonparametric approach to identification of Hammerstein and Wiener systems
Author
Chen, Han-Fu ; Hu, Xiao-Li
Author_Institution
Inst. of Syst. Sci., Chinese Acad. of Sci., Beijing, China
Volume
1
fYear
2005
fDate
26-29 June 2005
Firstpage
59
Abstract
Recursive identification algorithms are given for Hammerstein and Wiener systems with nonparametric nonlinearity f(·). All estimates derived from the algorithms for coefficients of the linear subsystem and for f(u) for any fixed u are strongly consistent.
Keywords
control nonlinearities; identification; linear systems; nonparametric statistics; stochastic systems; Hammerstein system identification; Wiener system identification; linear subsystem; nonparametric nonlinearity; recursive identification algorithm; Iterative methods; Linear systems; Mathematics; Nonlinear systems; Optimization methods; Parameter estimation; Piecewise linear techniques; Polynomials; Recursive estimation; Stochastic systems; Hammerstein system; Wiener system; nonparametric nonlinearity; recursive estimate; stochastic approximation; strong consistency;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation, 2005. ICCA '05. International Conference on
Print_ISBN
0-7803-9137-3
Type
conf
DOI
10.1109/ICCA.2005.1528092
Filename
1528092
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