Short communication: Improved global robust exponential stability criteria for interval neural networks with time-varying delays

Authors:
Jin-Liang Shao;Ting-Zhu Huang;Xiao-Ping Wang
Affiliations:
School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China;School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China;School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 7
Cited 1

Topics in matrix analysis

Topics in matrix analysis
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Robust stability for interval Hopfield neural networks with time delay

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Abstract

In this paper, by developing a new approach based on H-matrix theory, some improved sufficient conditions for global robust exponential stability of interval neural networks with time-varying delays are presented. Theoretic analysis shows that our results improve and generalize some previously published ones. Finally, some numerical examples are given to show the effectiveness of the obtained results.