DocumentCode
814491
Title
Chaotifying linear Elman networks
Author
Li, Xiang ; Chen, Guanrong ; Chen, Zengqiang ; Yuan, Zhuzhi
Author_Institution
Dept. of Autom., Nankai Univ., Tianjin, China
Volume
13
Issue
5
fYear
2002
fDate
9/1/2002 12:00:00 AM
Firstpage
1193
Lastpage
1199
Abstract
A linear model of recurrent neural networks, called the Elman networks, is combined with the simple nonlinear modulo (mod) operation on its linear activated function so as to generate chaos purposely. Conditions on the weight matrix are obtained, under which the generated chaos satisfies the mathematical definition of chaos in the sense of T.Y. Li and J.A. Yorke (1975). Some simple and representative weight matrices are constructed for designing such Elman networks that can generate Li-Yorke chaos. Several numerical simulations are shown to verify and visualize the design.
Keywords
chaos; matrix algebra; recurrent neural nets; Li-Yorke chaos; chaos; chaotification; linear Elman networks; linear activated function; linear model; mathematical definition; recurrent neural networks; simple nonlinear modulo operation; weight matrices; weight matrix; Automation; Biological neural networks; Chaos; Humans; Neurofeedback; Neurons; Numerical simulation; Recurrent neural networks; State feedback; Visualization;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/TNN.2002.1031950
Filename
1031950
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