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Global asymptotic stability of neural networks with delay: Comparative evaluation of two criteria

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  • Singh, Vimal

Abstract

In [IEEE Trans Circ Syst II 2005;52(4):181–4], a criterion for the global asymptotic stability of a class of delayed neural networks has been presented. The criterion is based on the factorization B=B1B2, where B denotes the delayed connection weight matrix. In the present paper, this criterion is compared with the criterion reported in [Phys Lett A 2003;311(6):504–11]. It turns out that, as far as the case of a nonsingular matrix B1 is concerned, these two criteria are one and the same.

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  • Singh, Vimal, 2007. "Global asymptotic stability of neural networks with delay: Comparative evaluation of two criteria," Chaos, Solitons & Fractals, Elsevier, vol. 31(5), pages 1187-1190.
    • Handle: RePEc:eee:chsofr:v:31:y:2007:i:5:p:1187-1190
    DOI: 10.1016/j.chaos.2006.01.045
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    Cited by:

    1. Singh, Vimal, 2009. "Remarks on estimating upper limit of norm of delayed connection weight matrix in the study of global robust stability of delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 39(5), pages 2013-2017.
    2. Singh, Vimal, 2009. "Novel global robust stability criterion for neural networks with delay," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 348-353.

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