Finite-time synchronization control of a class of memristor-based recurrent neural networks.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

This paper presents a global and local finite-time synchronization control law for memristor neural networks. By utilizing the drive-response concept, differential inclusions theory, and Lyapunov functional method, we establish several sufficient conditions for finite-time synchronization between the master and corresponding slave memristor-based neural network with the designed controller. In comparison with the existing results, the proposed stability conditions are new, and the obtained results extend some previous works on conventional recurrent neural networks. Two numerical examples are provided to illustrate the effective of the design method.

Authors

  • Minghui Jiang
    Department of Orthopedics, Third Hospital of Changsha, Changsha 410015.
  • Shuangtao Wang
    College of Science, China Three Gorges University, Yichang, Hubei 443002, China. Electronic address: wangshuangtaojy@163.com.
  • Jun Mei
    Centre of New Energy Systems, Department of Electrical and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa. Electronic address: meij0000@163.com.
  • Yanjun Shen
    College of Science, China Three Gorges University, Yichang, Hubei 443002, China.