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Reproducing chaos by variable structure recurrent neural networks
Ramon A Felix1, Edgar N Sanchez, Guanrong Chen
1CINVESTAV, Unidad Guadalajara, Mexico.
IEEE Transactions on Neural Networks
|November 30, 2004
Abstract:
In this paper, we present a new approach for chaos reproduction using variable structure recurrent neural networks (VSRNN). A neural network identifier is designed, with a variable structure that will change according to its output performance as compared to the given orbits of an unknown chaotic systems. A tradeoff between identification errors and computational complexity is discussed.
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