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Further stability analysis on Cohen–Grossberg neural networks with time-varying and distributed delays

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  • Tao Li
  • Aiguo Song
  • Shumin Fei

Abstract

The article is concerned with asymptotical stability for Cohen–Grossberg neural networks with both interval time-varying (0 ≤ τ0 ≤ τ(t) ≤ τm) and distributed delays, in which two types of distributed delays are treated: one is bounded while the other is unbounded. Through partitioning the delay intervals [0, τ0] and [τ0, τm], and choosing two augmented Lyapunov–Krasovskii functionals, some sufficient conditions are obtained to guarantee the global stability by employing the simplified free-weighting matrix method and convex combination. These stability criteria are presented in terms of linear matrix inequalities (LMIs) and can be easily checked by resorting to LMI in Matlab toolbox. Finally, three numerical examples are given to illustrate the effectiveness and reduced conservatism of the theoretical results.

Suggested Citation

  • Tao Li & Aiguo Song & Shumin Fei, 2011. "Further stability analysis on Cohen–Grossberg neural networks with time-varying and distributed delays," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(10), pages 1639-1649.
  • Handle: RePEc:taf:tsysxx:v:42:y:2011:i:10:p:1639-1649
    DOI: 10.1080/00207720903576514
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    Cited by:

    1. Shen Cong, 2014. "New stability criteria of linear singular systems with time-varying delay," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(9), pages 1927-1935, September.

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