Neural Networks2022,Vol.14510.DOI:10.1016/j.neunet.2021.10.015

Exponential synchronization of coupled neural networks under stochastic deception attacks

Zhang H. Li L. Li X.
Neural Networks2022,Vol.14510.DOI:10.1016/j.neunet.2021.10.015

Exponential synchronization of coupled neural networks under stochastic deception attacks

Zhang H. 1Li L. 1Li X.2
扫码查看

作者信息

  • 1. School of Mathematics Hefei University of Technology
  • 2. School of Mathematics and Statistics Shandong Normal University
  • 折叠

Abstract

? 2021 Elsevier LtdIn this paper, the issue of synchronization is investigated for coupled neural networks subject to stochastic deception attacks. Firstly, a general differential inequality with delayed impulses is given. Then, the established differential inequality is further extended to the case of delayed stochastic impulses, in which both the impulsive instants and impulsive intensity are stochastic. Secondly, by modeling the stochastic discrete-time deception attacks as stochastic impulses, synchronization criteria of the coupled neural networks under the corresponding attacks are given. Finally, two numerical examples are provided to demonstrate the correctness of the theoretical results.

Key words

Deception attacks/Neural networks/Stochastic impulses/Synchronization/Time delay

引用本文复制引用

出版年

2022
Neural Networks

Neural Networks

EISCI
ISSN:0893-6080
被引量27
参考文献量41
段落导航相关论文