Discrete-time recurrent high order neural networks for nonlinear identification
Identification
Nonlinear system identification
DOI:
10.1016/j.jfranklin.2010.05.018
Publication Date:
2010-06-11T08:57:49Z
AUTHORS (4)
ABSTRACT
This paper focuses on the problem of discrete-time nonlinear system identification via recurrent high order neural networks. It includes the respective stability analysis on the basis of the Lyapunov approach for the NN training algorithm. Applicability of the proposed scheme is illustrated via simulation for a discrete-time nonlinear model of an electric induction motor.
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