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Fixed-time synchronization of coupled memristive neural networks with multi-links and application in secure communication
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  • Hui Zhao,
  • Aidi Liu,
  • Qingjie Wang,
  • Mingwen Zheng,
  • Chuan Chen,
  • Baozhu Li,
  • Sijie Niu
Hui Zhao
University of Jinan
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Aidi Liu
University of Jinan
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Qingjie Wang
University of Jinan
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Mingwen Zheng
Shandong University of Technology
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Chuan Chen
Qilu University of Technology (Shandong Academy of Sciences)
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Baozhu Li
University of Jinan
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Sijie Niu
University of Jinan
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Abstract

This paper is devoted to investigating the issues of fixed-time synchronization of coupled memristive neural networks with multi-links (MCMNN). Based on the fixed-time stability criterion and the upper bound estimate formula for the settling time, we propose a secure communication scheme. The network with multi-links performance and coupled form increase the complexity of network topology and the unstable of systems, which improve security of communication in the aspect of encrypt the plaintext signal. We design a proper controller and build the Lyapunov function, several effective conditions are obtained to achieve the fixed-time synchronization of MCMNN. Moreover, the settling times can be estimated for fixed-time synchronization without depending on any initial values. Meanwhile, the plaintext signals can be recovered according to the fixed-time stability theorem. Finally, numerical simulations are given to verify the effectiveness of the theoretical results in fixed-time synchronization of MCMNN, and an example of a secure communication scheme is given to show the usability and superiority based on fixed-time stability theorem.

Peer review status:UNDER REVIEW

03 Mar 2021Submitted to Mathematical Methods in the Applied Sciences
03 Mar 2021Assigned to Editor
03 Mar 2021Submission Checks Completed
13 Mar 2021Reviewer(s) Assigned