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Adaptive anti-synchronization of memristor-based complex-valued neural networks with time delays

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  • Xu, Wei
  • Zhu, Song
  • Fang, Xiaoyu
  • Wang, Wei

Abstract

This paper mainly deals with the adaptive anti-synchronization problem of memristor-based complex-valued neural networks with time delays. By using the concept of adaptive control technology, a specific feedback controller is designed to achieve anti-synchronization. Compared to the anti-synchronization of complex-valued memristor-based delays neural networks, we use adaptive controller in the article. The adaptive controller can adjust system itself according to different updating laws. The obtained result is more reliable and improve some of the existing achievements. Finally, a numerical example is given to illustrate the effectiveness of the theoretical result.

Suggested Citation

  • Xu, Wei & Zhu, Song & Fang, Xiaoyu & Wang, Wei, 2019. "Adaptive anti-synchronization of memristor-based complex-valued neural networks with time delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    • Handle: RePEc:eee:phsmap:v:535:y:2019:i:c:s0378437119313974
    DOI: 10.1016/j.physa.2019.122427
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    References listed on IDEAS

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    Cited by:

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    2. Zhou, Wenjia & Hu, Yuanfa & Liu, Xiaoyang & Cao, Jinde, 2022. "Finite-time adaptive synchronization of coupled uncertain neural networks via intermittent control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    3. Ganesan, Bhuvaneshwari & Annamalai, Manivannan, 2023. "Anti-synchronization analysis of chaotic neural networks using delay product type looped-Lyapunov functional," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    4. Duan, Lian & Shi, Min & Huang, Chuangxia & Fang, Xianwen, 2021. "Synchronization in finite-/fixed-time of delayed diffusive complex-valued neural networks with discontinuous activations," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    5. Bashir Ahmad & Madeaha Alghanmi & Ahmed Alsaedi & Ravi P. Agarwal, 2019. "Nonlinear Impulsive Multi-Order Caputo-Type Generalized Fractional Differential Equations with Infinite Delay," Mathematics, MDPI, vol. 7(11), pages 1-15, November.
    6. Jun Guo & Yanchao Shi & Weihua Luo & Yanzhao Cheng & Shengye Wang, 2023. "Adaptive Global Synchronization for a Class of Quaternion-Valued Cohen-Grossberg Neural Networks with Known or Unknown Parameters," Mathematics, MDPI, vol. 11(16), pages 1-16, August.
    7. Mao, Kun & Liu, Xiaoyang & Cao, Jinde & Hu, Yuanfa, 2022. "Finite-time bipartite synchronization of coupled neural networks with uncertain parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    8. Pan, Jinsong & Zhang, Zhengqiu, 2021. "Finite-time synchronization for delayed complex-valued neural networks via the exponential-type controllers of time variable," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    9. Jingjing You & Abdujelil Abdurahman & Hayrengul Sadik, 2022. "Fixed/Predefined-Time Synchronization of Complex-Valued Stochastic BAM Neural Networks with Stabilizing and Destabilizing Impulse," Mathematics, MDPI, vol. 10(22), pages 1-20, November.
    10. Wang, Yang & Li, Huanyun & Guan, Yan & Chen, Mingshu, 2022. "Predefined-time chaos synchronization of memristor chaotic systems by using simplified control inputs," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    11. Li, Xuemei & Liu, Xinge & Wang, Fengxian, 2023. "Anti-synchronization of fractional-order complex-valued neural networks with a leakage delay and time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).

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