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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 14/2024

21.02.2024 | Original Article

Sliding mode synchronization of uncertain memristor cellular neural network and application in secure communication

verfasst von: Wei Zheng, Shaocheng Qu, Qian Tang

Erschienen in: Neural Computing and Applications | Ausgabe 14/2024

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Abstract

The purpose of this research is to investigate the synchronization and control for uncertain memristor-based cellular neural network and its application in secure communication. To address the issue, a novel sliding mode function is designed, on which the system states can effectively converge to the equilibrium point after reaching the sliding mode surface. Moreover, the corresponding controller is constructed by employing the proposed sliding mode function. The proposed control strategy achieves the synchronization of the uncertain memristor-based cellular neural network, and effectively addresses the integral saturation existing in traditional one. In addition, the control performance, including convergence speed, control accuracy, robustness and security, are significantly enhanced. Furthermore, the stability of the system is discussed based on Lyapunov theory. Finally, comparative tests and application examples are presented to verify the effectiveness of the proposed scheme.
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Metadaten
Titel
Sliding mode synchronization of uncertain memristor cellular neural network and application in secure communication
verfasst von
Wei Zheng
Shaocheng Qu
Qian Tang
Publikationsdatum
21.02.2024
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 14/2024
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-024-09500-9

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