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Optimal synchronization in small-world biological neural networks with time-varying weights

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  • Zheng, Hongyu
  • Luo, Xiaoshu

Abstract

In this paper, a new model of small-world biological neural networks based on biophysical Hodgkin–Huxley neurons with time-varying weights is proposed. Then the synchronization phenomenon of small-world biological neural networks evoked by the learning rate is studied. The study shows that there exists an optimal synchronization state by changing the learning rate.

Suggested Citation

  • Zheng, Hongyu & Luo, Xiaoshu, 2009. "Optimal synchronization in small-world biological neural networks with time-varying weights," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 516-520.
    • Handle: RePEc:eee:chsofr:v:41:y:2009:i:1:p:516-520
    DOI: 10.1016/j.chaos.2008.02.022
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    References listed on IDEAS

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    1. Perc, Matjaž, 2007. "Effects of small-world connectivity on noise-induced temporal and spatial order in neural media," Chaos, Solitons & Fractals, Elsevier, vol. 31(2), pages 280-291.
    2. Wang, Jiang & Chen, Liangquan & Fei, Xianyang, 2007. "Bifurcation control of the Hodgkin–Huxley equations," Chaos, Solitons & Fractals, Elsevier, vol. 33(1), pages 217-224.
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