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New chaotic memristive cellular neural network and its application in secure communication system

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  • Xiu, Chunbo
  • Zhou, Ruxia
  • Liu, Yuxia

Abstract

In order to improve the engineering feasibility of the memristive cellular neural network, a new memristor model with the smooth characteristic curve is designed. Based on the new memristor model, a new four-dimensional chaotic memristive cellular neural network (CNN) system is constructed, and its chaotic dynamic behaviors are analyzed. It can be applied to the secure communication based on the chaos synchronization control. Because both the external disturbances and uncertainties of internal parameters are maybe in the practical secure communication system, sliding mode control is used to perform the chaos synchronization between the sender and receiver. A new terminal sliding mode surface is designed to make the error system converge to zero in a finite time. Simulation results show that the new terminal sliding mode control has good robustness to the external disturbances and uncertainties of internal parameters, and the new chaotic memristive CNN system can be used in the secure communication by the chaos synchronization based on sliding mode control.

Suggested Citation

  • Xiu, Chunbo & Zhou, Ruxia & Liu, Yuxia, 2020. "New chaotic memristive cellular neural network and its application in secure communication system," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    • Handle: RePEc:eee:chsofr:v:141:y:2020:i:c:s0960077920307128
    DOI: 10.1016/j.chaos.2020.110316
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    5. Chen, Qun & Li, Bo & Yin, Wei & Jiang, Xiaowei & Chen, Xiangyong, 2023. "Bifurcation, chaos and fixed-time synchronization of memristor cellular neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    6. Cao, Hongli & Wang, Yu & Banerjee, Santo & Cao, Yinghong & Mou, Jun, 2024. "A discrete Chialvo–Rulkov neuron network coupled with a novel memristor model: Design, Dynamical analysis, DSP implementation and its application," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
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    8. Karnan, A. & Nagamani, G., 2022. "Non-fragile state estimation for memristive cellular neural networks with proportional delay," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 217-231.
    9. Hongbo Cao & Faqiang Wang, 2023. "An Overview of Complex Instability Behaviors Induced by Nonlinearity of Power Electronic Systems with Memristive Load," Energies, MDPI, vol. 16(6), pages 1-25, March.
    10. Zhang, Hai & Cheng, Yuhong & Zhang, Weiwei & Zhang, Hongmei, 2023. "Time-dependent and Caputo derivative order-dependent quasi-uniform synchronization on fuzzy neural networks with proportional and distributed delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 846-857.
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