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Global convergence of periodic solution of neural networks with discontinuous activation functions

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  • Huang, Lihong
  • Guo, Zhenyuan

Abstract

In this paper, without assuming boundedness and monotonicity of the activation functions, we establish some sufficient conditions ensuring the existence and global asymptotic stability of periodic solution of neural networks with discontinuous activation functions by using the Yoshizawa-like theorem and constructing proper Lyapunov function. The obtained results improve and extend previous works.

Suggested Citation

  • Huang, Lihong & Guo, Zhenyuan, 2009. "Global convergence of periodic solution of neural networks with discontinuous activation functions," Chaos, Solitons & Fractals, Elsevier, vol. 42(4), pages 2351-2356.
    • Handle: RePEc:eee:chsofr:v:42:y:2009:i:4:p:2351-2356
    DOI: 10.1016/j.chaos.2009.03.124
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    References listed on IDEAS

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    1. Zhang, Qiang & Wei, Xiaopeng & Xu, Jin, 2005. "New stability conditions for neural networks with constant and variable delays," Chaos, Solitons & Fractals, Elsevier, vol. 26(5), pages 1391-1398.
    2. Singh, Vimal, 2006. "Simplified LMI condition for global asymptotic stability of delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 29(2), pages 470-473.
    3. Park, Ju H., 2006. "On global stability criterion for neural networks with discrete and distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 30(4), pages 897-902.
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    Cited by:

    1. Wang, Jiafu & Huang, Lihong, 2012. "Almost periodicity for a class of delayed Cohen–Grossberg neural networks with discontinuous activations," Chaos, Solitons & Fractals, Elsevier, vol. 45(9), pages 1157-1170.

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