Robust stability results for uncertain stochastic neural networks with discrete interval and distributed time-varying delays

作者: R. Rakkiyappan , P. Balasubramaniam , S. Lakshmanan

DOI: 10.1016/J.PHYSLETA.2008.06.011

关键词: Stability resultLinear matrixApplied mathematicsLinear matrix inequalityBounded functionStochastic neural networkNorm (mathematics)Stochastic stabilityPhysics

摘要: Abstract This Letter is concerned with stability analysis problem for uncertain stochastic neural networks discrete interval and distributed time-varying delays. The parameter uncertainties are assumed to be norm bounded the delay belong a given interval, which means that lower upper bounds of delays available. Based on Lyapunov–Krasovskii functional theory, delay-interval dependent criteria obtained in terms linear matrix inequalities. Some formulated by feasibility inequality (LMI) introducing some free-weighting matrices. Finally, two numerical examples provided demonstrate less conservatism effectiveness proposed LMI conditions.

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