Existence and exponential stability of anti-periodic solutions of Hopfield neural networks with impulses

In this paper we investigate a class of Hopfield neural networks subject to periodic impulses. First we give sufficient conditions to ensure existence and exponential stability of the anti-periodic solutions, which are new and complementary to previously known results. Then we present an example to...

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Bibliographic Details
Published inApplied mathematics and computation Vol. 216; no. 2; pp. 623 - 630
Main Authors Shi, Peilin, Dong, Lingzhen
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier Inc 15.03.2010
Elsevier
Subjects
Anti-periodic solutions
Computation
Exact sciences and technology
Exponential stability
Hopfield neural networks
Impulses
Mathematical analysis
Mathematical models
Mathematics
Neural networks
Numerical analysis
Numerical analysis. Scientific computation
Sciences and techniques of general use
Stability
Impulses
Exponential stability
Anti-periodic solutions
Hopfield neural networks
Existence condition
Numerical analysis
Sufficient condition
Applied mathematics
Neural network
Periodic solution
Numerical stability
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ISSN0096-3003
1873-5649
DOI10.1016/j.amc.2010.01.095

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Summary:In this paper we investigate a class of Hopfield neural networks subject to periodic impulses. First we give sufficient conditions to ensure existence and exponential stability of the anti-periodic solutions, which are new and complementary to previously known results. Then we present an example to demonstrate our results.
Bibliography:ObjectType-Article-2
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ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2010.01.095