Global exponential synchronization of multiple memristive neural networks with time delay via nonlinear coupling.

Journal: IEEE transactions on neural networks and learning systems
Published Date:

Abstract

This paper presents theoretical results on the global exponential synchronization of multiple memristive neural networks with time delays. A novel coupling scheme is introduced, in a general topological structure described by a directed or undirected graph, with a linear diffusive term and discontinuous sign term. Several criteria are derived based on the Lyapunov stability theory to ascertain the global exponential stability of synchronization manifold in the coupling scheme. Simulation results for several examples are given to substantiate the effectiveness of the theoretical results.

Authors

  • 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.
  • Shaofu Yang
  • Jun Wang
    Department of Speech, Language, and Hearing Sciences and the Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA.