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A novel criterion for global asymptotic stability of BAM neural networks with time delays

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  • Park, Ju H.

Abstract

A delay-differential equation modelling a bidirectional associative memory (BAM) neural networks is investigated. An asymptotic stability of the BAM neural networks with time delays is considered by constructing a new suitable Lyapunov functional and some matrix inequality technique. A novel delay-dependent stability criterion is given in terms of matrix inequalities, which can be solved easily by various optimization algorithms.

Suggested Citation

  • Park, Ju H., 2006. "A novel criterion for global asymptotic stability of BAM neural networks with time delays," Chaos, Solitons & Fractals, Elsevier, vol. 29(2), pages 446-453.
    • Handle: RePEc:eee:chsofr:v:29:y:2006:i:2:p:446-453
    DOI: 10.1016/j.chaos.2005.08.018
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    References listed on IDEAS

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    1. Huang, Xia & Cao, Jinde & Huang, De-Shuang, 2005. "LMI-based approach for delay-dependent exponential stability analysis of BAM neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 24(3), pages 885-898.
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