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Reproducing chaos by variable structure recurrent neural networks

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3 Author(s)
R. A. Felix ; CINVESTAV, Guadalajara, Spain ; E. N. Sanchez ; Guanrong Chen

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.

Published in:

IEEE Transactions on Neural Networks  (Volume:15 ,  Issue: 6 )