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Adaptive synchronization of neural networks with time-varying delay and distributed delay

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  • Wang, Kai
  • Teng, Zhidong
  • Jiang, Haijun

Abstract

In this paper, the adaptive synchronization of neural networks with time-varying delay and distributed delay is discussed. Based on the LaSalle invariant principle of functional differential equations and the adaptive feedback control technique, some sufficient conditions for adaptive synchronization of such a system are obtained. Finally, a numerical example is given to show the effectiveness of the proposed synchronization method.

Suggested Citation

  • Wang, Kai & Teng, Zhidong & Jiang, Haijun, 2008. "Adaptive synchronization of neural networks with time-varying delay and distributed delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 631-642.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:2:p:631-642
    DOI: 10.1016/j.physa.2007.09.016
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    References listed on IDEAS

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    1. Lu, Jun-an & Han, Xiu-ping & Li, Yi-tian & Yu, Ming-hui, 2007. "Adaptive coupled synchronization among multi-Lorenz systems family," Chaos, Solitons & Fractals, Elsevier, vol. 31(4), pages 866-878.
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    4. Wang, Weiwei & Cao, Jinde, 2006. "Synchronization in an array of linearly coupled networks with time-varying delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 197-211.
    5. Li, Ping & Cao, Jinde & Wang, Zidong, 2007. "Robust impulsive synchronization of coupled delayed neural networks with uncertainties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 261-272.
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    Cited by:

    1. 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).
    2. Jian, Jigui & Wan, Peng, 2015. "Global exponential convergence of generalized chaotic systems with multiple time-varying and finite distributed delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 431(C), pages 152-165.
    3. Xueyan Zhao & Feiqi Deng, 2014. "New-type stability theorem for stochastic functional differential equations with application to SFDSs with distributed delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(5), pages 1156-1169, May.
    4. Zhang, Chuan & Wang, Xingyuan & Luo, Chao & Li, Junqiu & Wang, Chunpeng, 2018. "Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 251-264.
    5. Zhang, Yan-Jie & Liu, Song & Yang, Ran & Tan, Ying-Ying & Li, Xiaoyan, 2019. "Global synchronization of fractional coupled networks with discrete and distributed delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 830-837.
    6. Zhu, Ruiyuan & Guo, Yingxin & Wang, Fei, 2020. "Quasi-synchronization of heterogeneous neural networks with distributed and proportional delays via impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    7. Gosak, Marko & Markovič, Rene & Marhl, Marko, 2012. "The role of neural architecture and the speed of signal propagation in the process of synchronization of bursting neurons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2764-2770.
    8. Zhang, Chaolong & Deng, Feiqi & Peng, Yunjian & Zhang, Bo, 2015. "Adaptive synchronization of Cohen–Grossberg neural network with mixed time-varying delays and stochastic perturbation," Applied Mathematics and Computation, Elsevier, vol. 269(C), pages 792-801.

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