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The synchronization of a couple of hyperchaotic systems is studied. Based on Lyapunov stabilization theory, the sufficient conditions and range of the control parameters for self-synchronization of the hyperchaotic system are derived through nonlinear feedback control method when parameters of the system are known. Synchronization of the hyperchaotic systems can be achieved quickly by selecting appropriate...
International oil market is presented as a complex system with non-linear characteristics, in which oil price is affected by a set of different factors. In order to test if the international oil price chaotic or not, the phase space reconstruction technique (PSRT) is used to reorder the time series, and the methods of improved G-P algorithm, non-bias autocorrelation, Wolf algorithm and correlation...
To provide an ability to characterize local features for the chaotic neural network (CNN), Gauss wavelet is used for the self-feedback of the CNN with the dilation parameter acting as the bifurcation parameter. The exponentially decaying dilation parameter and the chaotically varying translation parameter not only govern the wavelet self-feedback transform but also enable the CNN to generate complex...
Wavelet chaotic neural network is a kind of chaotic neural network with non-monotonous activation function composed by Sigmoid and Wavelet. In this paper, wavelet chaotic neural network models with different nonlinear self-feedbacks are proposed and the effects of the different self-feedbacks on simulated annealing are analyzed respectively. Then the proposed models are applied to the 10-city traveling...
Chaotic neural network has been proved to be a powerful tool to solve combinational optimization problems. Wavelet chaotic neural network is a kind of chaotic neural network with non-monotonous activation function composed by Sigmoid and Wavelet. In this paper, first a wavelet chaotic neural network model with different nonlinear self-feedbacks is proposed and the effects of the different self-feedbacks...
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