Lag H synchronization in coupled reaction-diffusion neural networks with multiple state or derivative couplings.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date: Oct 10, 2022

Abstract

This paper mainly attempts to discuss lag H synchronization in multiple state or derivative coupled reaction-diffusion neural networks without and with parameter uncertainties. Firstly, we respectively propose two types of reaction-diffusion neural networks with multiple state and derivative couplings subject to parameter uncertainties. Secondly, by exploiting designed state feedback controllers, several criteria of the lag H synchronization for these two networks are developed based on Lyapunov functional and inequality techniques. Thirdly, lag H synchronization issues of these two networks are also coped with by virtue of devised adaptive control strategies. Finally, we provide two numerical examples to verify the obtained lag H synchronization criteria.

Authors

  • Lu Wang
    Department of Laboratory, Akesu Center of Disease Control and Prevention, Akesu, China.
  • Yougang Bian
    State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China; Wuxi Intelligent Control Research Institute of Hunan University, Wuxi 214115, China. Electronic address: byg10@foxmail.com.
  • Zhenyuan Guo
    College of Mathematics and Econometrics, Hunan University, Changsha, Hunan 410082, PR China; Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong. Electronic address: zyguo@hnu.edu.cn.
  • Manjiang Hu
    State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China; Wuxi Intelligent Control Research Institute of Hunan University, Wuxi 214115, China. Electronic address: manjiang_h@hnu.edu.cn.

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