Parameter-dependent robust stability of uncertain neural networks with time-varying delay |
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Authors: | Xuyang Lou Qian Ye Baotong Cui |
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Affiliation: | 1. Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing 400715, PR China;2. Texas A&M University at Qatar, Doha 23874, Qatar;3. College of Mathematics and Statistics, Chongqing Jiaotong University, Chongqing 400074, PR China;4. Department of Computer Science, Chongqing University of Education, Chongqing 400067, PR China |
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Abstract: | This paper is concerned with the problem of global robust asymptotic stability for delayed neural networks with polytopic parameter uncertainties and time-varying delay. A delay-dependent and parameter-dependent robust stability criterion for the equilibrium of delayed neural networks in the face of polytopic type uncertainties is presented by using a parameter-dependent Lyapunov functional and taking the relationship between the terms in the Leibniz–Newton formula into account. This criterion, expressed as a set of linear matrix inequalities, requires no matrix variable to be fixed for the entire uncertainty polytope, which produces a less conservative stability result. |
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