Global exponential stability for stochastic Cohen-Grossberg neural networks with multiple time-varying delays

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dc.categoryJournal Article
dc.contributor.authorSudamani Ramaswamy, A R
dc.date.accessioned2017-03-31T23:38:27Z
dc.date.available2017-03-31T23:38:27Z
dc.date.issued2012
dc.departmentMathematicsen_US
dc.description.abstractIn this paper, together with some Lyapunov functionals and effective mathematical techniques, sufficient conditions are derived to guarantee a class o f stochastic Cohen-Grossberg neural networks with multiple time-varying delays to be globally exponential stability by using linear matrix inequality (LMI) approach. Finally, a numerical example is provided to demonstrate the effectiveness o f the proposed method by using MATLAB LMI toolbox.en_US
dc.identifier.urihttps://ir.avinuty.ac.in/handle/avu/2483
dc.langEnglishen_US
dc.publisher.nameInternational Journal of Mathematical Modeling And Numerical Optimisationen_US
dc.publisher.typeInternationalen_US
dc.titleGlobal exponential stability for stochastic Cohen-Grossberg neural networks with multiple time-varying delaysen_US
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