Novel results on asymptotic stability and synchronization of fractional-order memristive neural networks with time delays: The 0<δ≤1 case.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date: Sep 7, 2023

Abstract

This paper investigates the asymptotic stability and synchronization of fractional-order (FO) memristive neural networks with time delays. Based on the FO comparison principle and inverse Laplace transform method, the novel sufficient conditions for the asymptotic stability of a FO nonlinear system are given. Then, based on the above conclusions, the sufficient conditions for the asymptotic stability and synchronization of FO memristive neural networks with time delays are investigated. The results in this paper have a wider coverage of situations and are more practical than the previous related results. Finally, the validity of the results is checked by two examples.

Authors

  • Jia-Rui Zhang
    Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, PR China; Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, PR China; Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai 200240, PR China.
  • Jun-Guo Lu
    Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, PR China; Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, PR China; Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai 200240, PR China. Electronic address: jglu@sjtu.edu.cn.
  • Xiao-Chuang Jin
    Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, PR China; Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, PR China; Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai 200240, PR China.
  • Xing-Yu Yang
    Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, PR China; Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, PR China; Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai 200240, PR China.

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