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Exponential p-stability of delayed Cohen–Grossberg-type BAM neural networks with impulses

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  • Xia, Yonghui
  • Huang, Zhenkun
  • Han, Maoan

Abstract

An impulsive Cohen–Grossberg-type bidirectional associative memory (BAM) neural networks with distributed delays is studied. Some new sufficient conditions are established for the existence and global exponential stability of a unique equilibrium without strict conditions imposed on self regulation functions. The approaches are based on Laypunov–Kravsovskii functional and homeomorphism theory. When our results are applied to the BAM neural networks, our results generalize some previously known results. It is believed that these results are significant and useful for the design and applications of Cohen–Grossberg-type bidirectional associative memory networks.

Suggested Citation

  • Xia, Yonghui & Huang, Zhenkun & Han, Maoan, 2008. "Exponential p-stability of delayed Cohen–Grossberg-type BAM neural networks with impulses," Chaos, Solitons & Fractals, Elsevier, vol. 38(3), pages 806-818.
    • Handle: RePEc:eee:chsofr:v:38:y:2008:i:3:p:806-818
    DOI: 10.1016/j.chaos.2007.01.009
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    References listed on IDEAS

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    1. Wang, Zidong & Shu, Huisheng & Liu, Yurong & Ho, Daniel W.C. & Liu, Xiaohui, 2006. "Robust stability analysis of generalized neural networks with discrete and distributed time delays," Chaos, Solitons & Fractals, Elsevier, vol. 30(4), pages 886-896.
    2. Liu, Jiang, 2005. "Global exponential stability of Cohen–Grossberg neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 26(3), pages 935-945.
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    Cited by:

    1. R. Sakthivel & R. Raja & S. M. Anthoni, 2011. "Exponential Stability for Delayed Stochastic Bidirectional Associative Memory Neural Networks with Markovian Jumping and Impulses," Journal of Optimization Theory and Applications, Springer, vol. 150(1), pages 166-187, July.
    2. R. Sakthivel & R. Raja & S. M. Anthoni, 2013. "Exponential Stability for Delayed Stochastic Bidirectional Associative Memory Neural Networks with Markovian Jumping and Impulses," Journal of Optimization Theory and Applications, Springer, vol. 158(1), pages 251-273, July.
    3. Li, Kelin & Zeng, Huanglin, 2010. "Stability in impulsive Cohen–Grossberg-type BAM neural networks with time-varying delays: A general analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(12), pages 2329-2349.
    4. Jian, Jigui & Wang, Baoxian, 2015. "Global Lagrange stability for neutral-type Cohen–Grossberg BAM neural networks with mixed time-varying delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 116(C), pages 1-25.
    5. Luo, Wenpin & Zhong, Shouming & Yang, Jun, 2009. "Global exponential stability of impulsive Cohen–Grossberg neural networks with delays," Chaos, Solitons & Fractals, Elsevier, vol. 42(2), pages 1084-1091.
    6. Huo, Hai-Feng & Li, Wan-Tong, 2009. "Dynamics of continuous-time bidirectional associative memory neural networks with impulses and their discrete counterparts," Chaos, Solitons & Fractals, Elsevier, vol. 42(4), pages 2218-2229.

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