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Adaptive synchronization of memristive neural networks with time-varying delays and reaction–diffusion term

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  • Tu, Zhengwen
  • Ding, Nan
  • Li, Liangliang
  • Feng, Yuming
  • Zou, Limin
  • Zhang, Wei

Abstract

This paper focuses on the synchronization control methodology for a class of delayed reaction–diffusion memristor-based neural networks. Adaptive controllers are designed such that the considered model can realize asymptotical and exponential synchronization goal under the framework of inequality techniques and Lyapunov method. The results obtained in this paper consider the effect of time delays as well as the reaction–diffusion terms, which generalize and improve some existing results. The derived synchronization criteria are presented in the form of algebraic, which can be easily verified. Finally, numerical example and its simulations are given to show the correctness of the obtained results.

Suggested Citation

  • Tu, Zhengwen & Ding, Nan & Li, Liangliang & Feng, Yuming & Zou, Limin & Zhang, Wei, 2017. "Adaptive synchronization of memristive neural networks with time-varying delays and reaction–diffusion term," Applied Mathematics and Computation, Elsevier, vol. 311(C), pages 118-128.
    • Handle: RePEc:eee:apmaco:v:311:y:2017:i:c:p:118-128
    DOI: 10.1016/j.amc.2017.05.005
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    References listed on IDEAS

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    Cited by:

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    2. Zhu, Sha & Bao, Haibo, 2022. "Event-triggered synchronization of coupled memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 415(C).
    3. Chen, Wei & Yu, Yongguang & Hai, Xudong & Ren, Guojian, 2022. "Adaptive quasi-synchronization control of heterogeneous fractional-order coupled neural networks with reaction-diffusion," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    4. Adel Ouannas & Mouna Abdelli & Zaid Odibat & Xiong Wang & Viet-Thanh Pham & Giuseppe Grassi & Ahmed Alsaedi, 2019. "Synchronization Control in Reaction-Diffusion Systems: Application to Lengyel-Epstein System," Complexity, Hindawi, vol. 2019, pages 1-8, February.
    5. Pahnehkolaei, Seyed Mehdi Abedi & Alfi, Alireza & Machado, J.A. Tenreiro, 2019. "Delay independent robust stability analysis of delayed fractional quaternion-valued leaky integrator echo state neural networks with QUAD condition," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 278-293.
    6. Qin, Xiaoli & Wang, Cong & Li, Lixiang & Peng, Haipeng & Yang, Yixian & Ye, Lu, 2018. "Finite-time modified projective synchronization of memristor-based neural network with multi-links and leakage delay," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 302-315.
    7. Feng, Yuming & Yang, Xinsong & Song, Qiang & Cao, Jinde, 2018. "Synchronization of memristive neural networks with mixed delays via quantized intermittent control," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 874-887.
    8. Wang, Yuxiao & Cao, Yuting & Guo, Zhenyuan & Huang, Tingwen & Wen, Shiping, 2020. "Event-based sliding-mode synchronization of delayed memristive neural networks via continuous/periodic sampling algorithm," Applied Mathematics and Computation, Elsevier, vol. 383(C).
    9. Li, Qiaoping & Liu, Sanyang & Chen, Yonggang, 2018. "Combination event-triggered adaptive networked synchronization communication for nonlinear uncertain fractional-order chaotic systems," Applied Mathematics and Computation, Elsevier, vol. 333(C), pages 521-535.
    10. Liu, Yamin & Xuan, Zuxing & Wang, Zhen & Zhou, Jianping & Liu, Yajuan, 2020. "Sampled-data exponential synchronization of time-delay neural networks subject to random controller gain perturbations," Applied Mathematics and Computation, Elsevier, vol. 385(C).

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