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Chin. Phys. B, 2021, Vol. 30(12): 120503    DOI: 10.1088/1674-1056/abfa09
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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.
Keywords:  adaptive synchronization      fractional calculus      complex-valued chaotic neural networks      time-delay  
Received:  02 March 2021      Revised:  08 April 2021      Accepted manuscript online:  21 April 2021
PACS:  05.45.Gg (Control of chaos, applications of chaos)  
  05.45.Pq (Numerical simulations of chaotic systems)  
  05.45.Xt (Synchronization; coupled oscillators)  
Fund: Project supported by the Science and Technology Support Program of Xingtai, China (Grant No. 2019ZC054).
Corresponding Authors:  Shi-Ping Yang     E-mail:

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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