Exponential stabilization of neural networks with various activation functions and mixed time-varying delays
journal contributionposted on 2010-07-01, 00:00 authored by V Phat, Hieu TrinhHieu Trinh
This paper presents some results on the global exponential stabilization for neural networks with various activation functions and time-varying continuously distributed delays. Based on augmented time-varying Lyapunov-Krasovskii functionals, new delay-dependent conditions for the global exponential stabilization are obtained in terms of linear matrix inequalities. A numerical example is given to illustrate the feasibility of our results.
JournalIEEE transactions on neural networks
Pagination1180 - 1184
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Publication classificationC1 Refereed article in a scholarly journal
Copyright notice2010, IEEE
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linear matrix inequalitieslyapunov functionmixed delayneural networksstabilizationScience & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer Science, Hardware & ArchitectureComputer Science, Theory & MethodsEngineering, Electrical & ElectronicComputer ScienceEngineeringGLOBAL STABILITY-CRITERIONROBUST STABILITYDISCRETESYSTEMS