作者: R. Rakkiyappan , P. Balasubramaniam , S. Lakshmanan
DOI: 10.1016/J.PHYSLETA.2008.06.011
关键词: Stability result 、 Linear matrix 、 Applied mathematics 、 Linear matrix inequality 、 Bounded function 、 Stochastic neural network 、 Norm (mathematics) 、 Stochastic stability 、 Physics
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.