Title:
using-adaptive-chebyshev
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- 2012-11-26
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Description: A novel algorithm for controlling Logistic chaotic system based on adaptive Chebyshev polynomials
neural networks (ACNN) is presented. In the algorithm, the activation function of hidden units is defined by Chebyshev
orthogonal polynomials in the neural networks, and the forecast and control model of Logistic chaotic system is estab-
lished. In order to ensure stability of the algorithm, the convergence theorem of the algorithm is proposed and proved.
Then the adaptive learning rate algorithm is used for improving the learning efficiency and convergence speed. The
adaptive Chebyshev neural networks directly learn dynamic characters of Logistic chaotic system and control it to target
function. The simulation results show that the algorithm is still effective when there are external disturbance in the Lo-
gistic chaotic system, now the learning time is 0.178s, training steps is 10 and mean square error is 1.15×10 − 4 . Com-
pared with other ordinary
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Algorithm for controlling logistic system using adaptive chebyshev.pdf
