Novel delay-dependent asymptotic stability criteria for neural networks with time-varying delays

The problem of delay-dependent asymptotic stability criteria for neural networks (NNs) with time-varying delays is investigated. An improved linear matrix inequality based on delay-dependent stability test is introduced to ensure a large upper bound for time-delay. A new class of Lyapunov function i...

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Bibliographic Details
Published in:Journal of computational and applied mathematics 2009-06, Vol.228 (1), p.133-138
Main Authors: Tian, Junkang, Xu, Dongsheng, Zu, Jian
Format: Article
Language:English
Subjects:
Delay-dependent
Exact sciences and technology
Linear matrix inequality (LMI)
Mathematical analysis
Mathematics
Neural networks (NNs)
Numerical analysis
Numerical analysis. Scientific computation
Sciences and techniques of general use
Time-varying delay
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Summary:The problem of delay-dependent asymptotic stability criteria for neural networks (NNs) with time-varying delays is investigated. An improved linear matrix inequality based on delay-dependent stability test is introduced to ensure a large upper bound for time-delay. A new class of Lyapunov function is constructed to derive a novel delay-dependent stability criteria. Finally, numerical examples are given to indicate significant improvement over some existing results.
ISSN:0377-0427
1879-1778
DOI:10.1016/j.cam.2008.09.002