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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Vydané v:	Neurocomputing (Amsterdam) Ročník 580; s. 127524
Hlavný autor:	Kumar, Rajesh
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.05.2024
Predmet:	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
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