DocumentCode :
3242150
Title :
Approximating nonlinear systems by nonlinear ARMA and AR models
Author :
DeGroat, Ronald D. ; Hunt, Louis R. ; Linebarger, Darel A.
Author_Institution :
Center for Eng. Math., Texas Univ., Richardson, TX, USA
Volume :
5
fYear :
1992
fDate :
23-26 Mar 1992
Firstpage :
465
Abstract :
A nonlinear autoregressive (AR) and AR moving average (ARMA) approximation theory is developed for an important class of nonlinear systems, namely, feedback linearizable systems with polynomial nonlinearities. The focus is on nonlinear AR models (NAR) because (1) the NAR parameters can be estimated via linear equations, (2) NAR models can be used to approximate almost any nonlinear system, and (3) compact difference equation and state space forms exist for this class of models
Keywords :
approximation theory; difference equations; nonlinear systems; parameter estimation; polynomials; signal processing; approximation theory; autoregressive models; autoregressive moving average models; compact difference equation; feedback linearizable systems; linear equations; nonlinear systems; parameter estimation; polynomial nonlinearities; signal processing; state space forms; Difference equations; Ear; Feedback; Linear systems; Mathematical model; Nonlinear control systems; Nonlinear systems; Polynomials; Signal processing; State-space methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location :
San Francisco, CA
ISSN :
1520-6149
Print_ISBN :
0-7803-0532-9
Type :
conf
DOI :
10.1109/ICASSP.1992.226582
Filename :
226582
Link To Document :
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