Delay-dependent exponential stability of delayed neural networks with time-varying delay

In this brief, free-weighting matrices are employed to express the relationship between the terms in the Leibniz-Newton formula; and based on that relationship, a new delay-dependent exponential-stability criterion is derived for delayed neural networks with a time-varying delay. Two numerical examp...

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Bibliographic Details
Published inIEEE transactions on circuits and systems. II, Express briefs Vol. 53; no. 7; pp. 553 - 557
Main Authors He, Yong, Wu, Min, She, Jin-Hua
Format Journal Article
LanguageEnglish
Published New York IEEE 01.07.2006
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Asymptotic stability
Circuits
Convergence
Criteria
Delay
Delay effects
Delay-dependent criterion
Educational programs
exponential stability
free-weighting matrix approach
Information science
Linear matrix inequalities
linear matrix inequality (LMI)
Mathematical analysis
Mathematical models
Matrices
Neural networks
Neurons
Stability
Stability criteria
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Summary:In this brief, free-weighting matrices are employed to express the relationship between the terms in the Leibniz-Newton formula; and based on that relationship, a new delay-dependent exponential-stability criterion is derived for delayed neural networks with a time-varying delay. Two numerical examples demonstrate the improvement this method provides over existing ones.
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ISSN:1549-7747
1558-3791
DOI:10.1109/TCSII.2006.876385