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New delay-dependent exponential stability criteria for neural networks with discrete and distributed time-varying delays
Authors:Junkang TianAuthor Vitae  Shouming ZhongAuthor Vitae
Affiliation:a School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China
b Key Laboratory for Neuroinformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China
Abstract:In this paper, the problem of exponential stability criteria for neural networks with discrete and distributed time-varying delays are considered. By dividing the discrete delay interval into multiple segments and choosing a new class of Lyapunov functional which contains tripe-integral terms, some new delay-dependent stability criteria are derived in terms of linear matrix inequalities. The obtained criteria are less conservative because free-weighting matrices method and a convex optimization approach are considered. Finally, numerical examples are given to illustrate the effectiveness of the proposed method.
Keywords:Exponential stability  Neural networks  Time-varying delays  Linear matrix inequality (LMI)
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