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

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• 作者：Jin-Liang  ; Shao ;   ; ^{jinliangshao@126.com} ; Ting-Zhu  ; Huang  ; ;   ; ^{tzhuang@uestc.edu.cn} ;   ; ^{tingzhuhuang@126.com} ; Xiao-Ping  ; Wang
• 关键词：Interval neural networks ; Global robust exponential stability ; H-matrix ; Linear matrix inequality (LMI)
• 刊名：Expert Systems with Applications
• 出版年：2011
• 出版时间：November-December 2011
• 年：2011
• 卷：38
• 期：12
• 页码：15587-15593
• 全文大小：339 K

文摘

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.