Adaptive event-triggered synchronization of neural networks under stochastic cyber-attacks with application to Chua's circuit.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date: Jul 8, 2023

Abstract

This paper focuses on the synchronization control problem for neural networks (NNs) subject to stochastic cyber-attacks. Firstly, an adaptive event-triggered scheme (AETS) is adopted to improve the utilization rate of network resources, and an output feedback controller is constructed for improving the performance of the system subject to the conventional deception attack and accumulated dynamic cyber-attack. Secondly, the synchronization problem of master-slave NNs is transformed into the stability analysis problem of the synchronization error system. Thirdly, by constructing a customized Lyapunov-Krasovskii functional (LKF), the adaptive event-triggered output feedback controller is designed to ensure the synchronization error system is asymptotically stable with a given H performance index. Lastly, in the simulation part, two examples, including Chua's circuit, illustrate the feasibility and universality of the related technologies in this paper.

Authors

  • Yao Xu
    Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
  • Chunyu Yang
    School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China.
  • Linna Zhou
    School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China; Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, Xuzhou, 221116, China. Electronic address: linnazhou@cumt.edu.cn.
  • Lei Ma
    School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China. Electronic address: leima@wit.edu.cn.
  • Song Zhu
    College of Sciences, China University of Mining and Technology, Xuzhou, 221116, China. Electronic address: songzhu82@gmail.com.

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