Global exponential stability of neural networks with time-varying delay based on free-matrix-based integral inequality

This paper is concerned with global exponential stability problem for a class of neural networks with time-varying delays. Using a new proposed inequality called free-matrix-based integral inequality, a less conservative criterion is proposed, which is expressed by linear matrix inequalities. Two nu...

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Bibliographic Details
Published inNeural networks Vol. 77; pp. 80 - 86
Main Authors He, Yong, Ji, Meng-Di, Zhang, Chuan-Ke, Wu, Min
Format Journal Article
LanguageEnglish
Published United States Elsevier Ltd 01.05.2016
Subjects
Algorithms
Criteria
Delay
Exponential stability
Inequalities
Integrals
Linear matrix inequalities
Lyapunov–Krasovskii functional
Neural networks
Neural Networks (Computer)
Stability
Time-varying delay
Exponential stability
Neural networks
Time-varying delay
Lyapunov–Krasovskii functional
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Summary:This paper is concerned with global exponential stability problem for a class of neural networks with time-varying delays. Using a new proposed inequality called free-matrix-based integral inequality, a less conservative criterion is proposed, which is expressed by linear matrix inequalities. Two numerical examples are given to show the effectiveness and superiority of the obtained criterion.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0893-6080
1879-2782
DOI:10.1016/j.neunet.2016.02.002