Adaptive synchronization of a class of fractional-order complex-valued chaotic neural network with time-delay
Mei Li(李梅)1,2, Ruo-Xun Zhang(张若洵)3, and Shi-Ping Yang(杨世平)1,†
1 College of Physics, Hebei Normal University, Shijiazhuang 050024, China; 2 Department of Computer Science, North China Electric Power University, Baoding 071003, China; 3 College of Primary Education, Xingtai University, Xingtai 054001, China
Abstract This paper is concerned with the adaptive synchronization of fractional-order complex-valued chaotic neural networks (FOCVCNNs) with time-delay. The chaotic behaviors of a class of fractional-order complex-valued neural network are investigated. Meanwhile, based on the complex-valued inequalities of fractional-order derivatives and the stability theory of fractional-order complex-valued systems, a new adaptive controller and new complex-valued update laws are proposed to construct a synchronization control model for fractional-order complex-valued chaotic neural networks. Finally, the numerical simulation results are presented to illustrate the effectiveness of the developed synchronization scheme.
Fund: Project supported by the Science and Technology Support Program of Xingtai, China (Grant No. 2019ZC054).
Corresponding Authors:
Shi-Ping Yang
E-mail: yangship@hebtu.edu.cn
Cite this article:
Mei Li(李梅), Ruo-Xun Zhang(张若洵), and Shi-Ping Yang(杨世平) Adaptive synchronization of a class of fractional-order complex-valued chaotic neural network with time-delay 2021 Chin. Phys. B 30 120503
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