Synchronous Control of Hysteretic Creep Chaotic Neural Network

A chaotic neuron with hysteretic and creep characteristics is proposed based on the conventional chaotic neuron model, with which a neural network is constructed, and the synchronous control between the hysteretic creep chaotic neuron or neural network and the deterministic chaotic neuron or neural...

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Bibliographic Details
Published in:	IEEE access 2016, Vol.4, p.8617-8624
Main Authors:	Xiu, Chunbo, Hou, Jianguo, Zang, Yakun, Xu, Guowei, Liu, Chang
Format:	Article
Language:	eng
Subjects:	Biological neural networks chaos Chaos theory Control stability Control theory creep Creep (materials) Fuzzy control Hysteresis Lyapunov methods Mathematical model Neural networks Parameter uncertainty Sliding mode control Stability analysis Synchronization synchronous
Online Access:	Get full text
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Summary:	A chaotic neuron with hysteretic and creep characteristics is proposed based on the conventional chaotic neuron model, with which a neural network is constructed, and the synchronous control between the hysteretic creep chaotic neuron or neural network and the deterministic chaotic neuron or neural network is investigated by the sliding mode control. The hysteretic activation function of the neuron is constructed by shifting the sigmoid function. The hysteretic parameters have creep properties, which lead to the uncertain responses of the neurons. The equivalent sliding mode control law can be designed according to the error equation of the synchronous system, and the Lyapunov method is used to prove the stability of the system. Furthermore, fuzzy sliding mode control law is designed to restrain the chattering, to reduce the synchronous error, as well as to shorten the transition time. The validity of this method has been proved by simulation experiments.
ISSN:	2169-3536 2169-3536