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Event-triggered hybrid impulsive control on lag synchronization of delayed memristor-based bidirectional associative memory neural networks for image hiding

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  • Yuan, Manman
  • Luo, Xiong
  • Mao, Xue
  • Han, Zhen
  • Sun, Lei
  • Zhu, Peican

Abstract

Memristor-based bidirectional associative memory neural networks (MBAMNNs) analysis can help to reveal the dynamic basis of secure communication. Effectively representing the synchronization of MBAMNNs is the principal task of applying brain-inspired neural networks to image hiding. Previous research has typically utilized continuous control methods to represent the synchronization of MBAMNNs, but these are not well coordinated under limited network bandwidth. Besides, the special communication features and uncertainties of MBAMNNs will affect the image encryption/decryption by introducing the concept of chaos synchronization for image hiding, but few studies have explored such elements. To address these two issues, we propose an event-triggered hybrid impulsive scheme on lag synchronization for image hiding. Specifically, we incorporate both time-varying uncertainties and the multi-layer topology structure of MBAMNNs into a designed event-triggered scheme. The frequency of the controller can be automatically updated from two novel triggered conditions, and Zeno-behavior can be avoided effectively. Experimental results demonstrate that our scheme not only outperforms several exciting approaches in synchronization but also can effectively realize the image hiding under low energy consumption.

Suggested Citation

  • Yuan, Manman & Luo, Xiong & Mao, Xue & Han, Zhen & Sun, Lei & Zhu, Peican, 2022. "Event-triggered hybrid impulsive control on lag synchronization of delayed memristor-based bidirectional associative memory neural networks for image hiding," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    • Handle: RePEc:eee:chsofr:v:161:y:2022:i:c:s0960077922005215
    DOI: 10.1016/j.chaos.2022.112311
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    References listed on IDEAS

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    1. Yuan, Manman & Wang, Weiping & Luo, Xiong & Liu, Linlin & Zhao, Wenbing, 2018. "Finite-time anti-synchronization of memristive stochastic BAM neural networks with probabilistic time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 244-260.
    2. Mazloom, Sahar & Eftekhari-Moghadam, Amir Masud, 2009. "Color image encryption based on Coupled Nonlinear Chaotic Map," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1745-1754.
    3. Zhu, Sha & Bao, Haibo, 2022. "Event-triggered synchronization of coupled memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 415(C).
    4. Wang, Weiping & Sun, Yue & Yuan, Manman & Wang, Zhen & Cheng, Jun & Fan, Denggui & Kurths, Jürgen & Luo, Xiong & Wang, Chunyang, 2021. "Projective synchronization of memristive multidirectional associative memory neural networks via self-triggered impulsive control and its application to image protection," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
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    Cited by:

    1. Xiang, Jianglian & Ren, Junwu & Tan, Manchun, 2022. "Stability analysis for memristor-based stochastic multi-layer neural networks with coupling disturbance," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    2. Zhang, Jianlin & Bao, Han & Yu, Xihong & Chen, Bei, 2024. "Heterogeneous coexistence of extremely many attractors in adaptive synapse neuron considering memristive EMI," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    3. Abed-Elhameed, Tarek M. & Mahmoud, Gamal M. & Elbadry, Motaz M. & Ahmed, Mansour E., 2023. "Nonlinear distributed-order models: Adaptive synchronization, image encryption and circuit implementation," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    4. Fang, Qi & Wang, Mingzhu & Li, Xiaodi, 2023. "Event-triggered distributed delayed impulsive control for nonlinear systems with applications to complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).

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