New stability criteria of neural networks with interval time-varying delay: A piecewise delay method

This paper provides improved conditions for the global asymptotic stability of a class of neural networks with interval time-varying delays. A piecewise delay method is firstly proposed. In this method, the variation interval of the time delay is divided into two subintervals by introducing its cent...

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Bibliographic Details
Published in:Applied mathematics and computation 2009-02, Vol.208 (1), p.249-259
Main Authors: Zhang, Yijun, Yue, Dong, Tian, Engang
Format: Article
Language:English
Subjects:
Delay-dependent
Exact sciences and technology
Interval delay
LMI
Mathematical analysis
Mathematics
Neural networks
Numerical analysis
Numerical analysis. Scientific computation
Sciences and techniques of general use
Stability
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Summary:This paper provides improved conditions for the global asymptotic stability of a class of neural networks with interval time-varying delays. A piecewise delay method is firstly proposed. In this method, the variation interval of the time delay is divided into two subintervals by introducing its central point. Then, by constructing a new Lyapunov–Krasovskii functional and checking its variation in the two subintervals, respectively, some new delay-dependent stability criteria for the addressed neural networks are derived. Numerical examples are provided to show that the achieved conditions are less conservative than some existing ones in the literature.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2008.11.046