Recurrent context layered radial basis function neural network for the identification of nonlinear dynamical systems

This paper proposes a novel recurrent context layered radial basis function neural network (RCLRBFNN) for the identification of nonlinear dynamical systems. The proposed model consists of an additional context layer in which the nodes represent the unit-delayed outputs of the hidden layer radial cen...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 580; S. 127524
1. Verfasser:	Kumar, Rajesh
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.05.2024
Schlagworte:	Adaptive learning rate Back-propagation algorithm Feed-forward and Jordan recurrent neural network Nonlinear system identification Recurrent radial basis function neural network Adaptive learning rate Feed-forward and Jordan recurrent neural network Back-propagation algorithm Recurrent radial basis function neural network Nonlinear system identification
ISSN:	0925-2312, 1872-8286
Online-Zugang:	Volltext
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