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Zbl 1222.93178
Xu, Shengyuan; Lam, James; Ho, Daniel W.C.
Novel global robust stability criteria for interval neural networks with multiple time-varying delays. (English)
[J] Phys. Lett., A 342, No. 4, 322-330 (2005). ISSN 0375-9601

Summary: This Letter is concerned with the problem of robust stability analysis for interval neural networks with multiple time-varying delays and parameter uncertainties. The parameter uncertainties are assumed to be bounded in given compact sets and the activation functions are supposed to be bounded and globally Lipschitz continuous. A sufficient condition is obtained by means of Lyapunov functionals, which guarantees the existence, uniqueness and global asymptotic stability of the delayed neural network for all admissible uncertainties. This condition is in terms of a linear matrix inequality (LMI), which can be easily checked by using recently developed algorithms in solving LMIs. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method.

MSC 2000:: *93D09 Robust stability of control systems
34K35 Functional-differential equations connected with control problems

Keywords: global asymptotic stability; interval systems; linear matrix inequality; neural networks; time-varying delays

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