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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40990

Title: Application of Genetic Algorithm and Recurrent Network to Nonlinear System Identification
Authors: Jih-Gau Juang
Contributors: 國立臺灣海洋大學:通訊與導航工程學系
Date: 2003
Issue Date: 2017-02-07T08:47:00Z
Publisher: Control Applications, 2003. CCA 2003. Proceedings of 2003 IEEE Conference on
Abstract: Abstract: Nonlinear system identification using recurrent neural network with genetic algorithm is presented. A continuous-time model of Hopfield neural network is used in this study. Its convergence properties are first evaluated. Then the model is implemented to identify nonlinear systems. Recurrent network's operational factors of the system identification scheme are obtained by genetic algorithm. Mathematical formulations are introduced throughout the paper. After test, the proposed scheme can successfully identify nonlinear system within acceptable tolerance.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40990
Appears in Collections:[通訊與導航工程學系] 演講及研討會

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