Synchronization of coupled switched neural networks subject to hybrid stochastic disturbances.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date: Aug 1, 2023

Abstract

In this paper, the theoretical analysis on exponential synchronization of a class of coupled switched neural networks suffering from stochastic disturbances and impulses is presented. A control law is developed and two sets of sufficient conditions are derived for the synchronization of coupled switched neural networks. First, for desynchronizing stochastic impulses, the synchronization of coupled switched neural networks is analyzed by Lyapunov function method, the comparison principle and a impulsive delay differential inequality. Then, for general stochastic impulses, by partitioning impulse interval and using the convex combination technique, a set of sufficient condition on the basis of linear matrix inequalities (LMIs) is derived for the synchronization of coupled switched neural networks. Eventually, two numerical examples and a practical application are elaborated to illustrate the effectiveness of the theoretical results.

Authors

  • Han Long
    College of Science, National University of Defense Technology, Changsha 410073, China. Electronic address: longhan@nudt.edu.cn.
  • Jingxuan Ci
    College of Mathematics and Hunan Provincial Key Laboratory of Intelligent information processing and Applied Mathematics, Hunan University, Changsha, China. Electronic address: jxci@hnu.edu.cn.
  • 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.
  • Shiping Wen
  • Tingwen Huang

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