Recurrent fuzzy-neural approach for nonlinear control using dynamic structure learning scheme

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Please use this identifier to cite or link to this item: http://chur.chu.edu.tw/handle/987654321/33463

Title:	Recurrent fuzzy-neural approach for nonlinear control using dynamic structure learning scheme
Authors:	許駿飛 Hsu, Chun-Fei
Contributors:	電機工程學系 Electrical Engineering
Keywords:	recurrent fuzzy neural network;nonlinear control;dynamic node construction
Date:	2007
Issue Date:	2014-06-27 02:23:27 (UTC+8)
Abstract:	In this paper, a dynamic recurrent fuzzy neural network (DRFNN) with a structure learning scheme is proposed. The structure learning scheme consists of two learning phases: the node-constructing phase and the node-pruning phase, which enables the DRFNN to
Appears in Collections:	[Department of Electrical Engineering] Journal Articles

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