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Existence and globally exponential stability of equilibrium for BAM neural networks with impulses

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

Abstract

In this paper, a class of two-layer heteroassociative networks called bidirectional associative memory (BAM) networks with impulses is studied. Some new sufficient conditions are established for the existence and globally exponential stability of a unique equilibrium, which generalize and improve the previously known results. The sufficient conditions are easy to verify and when the impulsive jumps are absent the results reduce to those of the non-impulsive systems. The approaches are based on employing Banach’s fixed point theorem, matrix theory and its spectral theory. Our results generalize and significantly improve the previous known results due to this method. Examples are given to show the feasibility and effectiveness of our results.

Suggested Citation

  • Xia, Yonghui & Huang, Zhenkun & Han, Maoan, 2008. "Existence and globally exponential stability of equilibrium for BAM neural networks with impulses," Chaos, Solitons & Fractals, Elsevier, vol. 37(2), pages 588-597.
    • Handle: RePEc:eee:chsofr:v:37:y:2008:i:2:p:588-597
    DOI: 10.1016/j.chaos.2006.08.045
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    References listed on IDEAS

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    1. Xia, Yonghui & Cao, Jinde & Lin, Muren, 2007. "New results on the existence and uniqueness of almost periodic solution for BAM neural networks with continuously distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 31(4), pages 928-936.
    2. Li, Yongkun, 2005. "Global exponential stability of BAM neural networks with delays and impulses," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 279-285.
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    Cited by:

    1. Wen, Zhen & Sun, Jitao, 2009. "Stability analysis of delayed Cohen–Grossberg BAM neural networks with impulses via nonsmooth analysis," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1829-1837.
    2. Zeng, Xu & Li, Chuandong & Huang, Tingwen & He, Xing, 2015. "Stability analysis of complex-valued impulsive systems with time delay," Applied Mathematics and Computation, Elsevier, vol. 256(C), pages 75-82.
    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. Xia, Yonghui & Wong, Patricia J.Y., 2009. "Global exponential stability of a class of retarded impulsive differential equations with applications," Chaos, Solitons & Fractals, Elsevier, vol. 39(1), pages 440-453.
    5. Zhang, Qianhong & Luo, Wei, 2009. "Global exponential stability of fuzzy BAM neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 42(4), pages 2239-2245.

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