New delay-dependent exponential stability criteria for neural networks with discrete and distributed time-varying delays |
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Authors: | Junkang TianAuthor Vitae Shouming ZhongAuthor Vitae |
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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 |
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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. |
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Keywords: | Exponential stability Neural networks Time-varying delays Linear matrix inequality (LMI) |
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