Abstract
This paper deals with 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 extended Kalman filter (EKF)-based NN training algorithm, which is applied for learning Applicability of the scheme is illustrated via simulation for a discrete-time nonlinear model of an electric induction motor.
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