DocumentCode
1379788
Title
Parametric Identification of Hammerstein Systems With Consistency Results Using Stochastic Inputs
Author
Zhao, Wen-Xiao
Author_Institution
Dept. of Autom., Tsinghua Univ., Beijing, China
Volume
55
Issue
2
fYear
2010
Firstpage
474
Lastpage
480
Abstract
The extended least squares algorithm is applied to identify the Hammerstein system, where the nonlinear static function f(??) is expressed as a linear combination of basic functions with unknown coefficients. Strong consistency of the estimates is established and their convergent rates are obtained as well.
Keywords
convergence; identification; least squares approximations; stochastic processes; Hammerstein systems; basic functions; consistency results; convergent rates; extended least squares algorithm; linear combination; nonlinear static function; parametric identification; stochastic inputs; strong consistency; unknown coefficients; Algorithm design and analysis; Approximation algorithms; Biological system modeling; Brain modeling; Finite impulse response filter; Least squares methods; Power engineering and energy; Power system modeling; Recursive estimation; Stochastic systems; ARMAX; Hammerstein system; extended least squares (ELS); strong consistency;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.2009.2036380
Filename
5378462
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