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Shao, Jin-Liang; Huang, Ting-Zhu; Zhou, Sheng

Some improved criteria for global robust exponential stability of neural networks with time-varying delays. (English) Zbl 1222.93175

Commun. Nonlinear Sci. Numer. Simul. 15, No. 12, 3782-3794 (2010).
Summary: Some sufficient conditions for global robust exponential stability of interval neural networks with time-varying delays are presented. It is shown that our results include some counterparts of the previous literature. On basis of the obtained results, some linear matrix inequality (LMI) criteria are derived. Moreover, three numerical examples and a simulation are given to show the effectiveness of the obtained results.

Cited in 10 Documents

MSC:

93D09 Robust stability
34K20 Stability theory of functional-differential equations
92B20 Neural networks for/in biological studies, artificial life and related topics
93C23 Control/observation systems governed by functional-differential equations

Keywords:

interval neural networks; time-varying delays; global robust exponential stability; nonnegative matrix; linear matrix inequality; Halanay inequality

Software:

LMI toolbox
PDF BibTeX XML Cite
\textit{J.-L. Shao} et al., Commun. Nonlinear Sci. Numer. Simul. 15, No. 12, 3782--3794 (2010; Zbl 1222.93175)
Full Text: DOI

References:

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