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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/12973

Title: Delay-Dependent Robust Stability for Uncertain Discrete Stochastic Recurrent Neural Networks with Interval Time-Varying Delays
Authors: Lu, Chien-Yu;Shyr, Wen-Jye;Yao, Kai-chao;Chen, Der-Fa
Contributors: 工業教育與技術學系
Keywords: Discrete stochastic recurrent neural networks;Interval time-varying delays;Linear matrix inequality;Robuststability;Uncertainty
Date: 2009-09
Issue Date: 2012-08-07T01:12:51Z
Publisher: ICIC Express Letters Office
Abstract: This paper considers the problem of global robust delay-dependent stabilityfor uncertain discrete stochastic recurrent neural networks with intervaltime-varying delays. The parameter uncertainties are assumed to be time-varyingnorm-bounded in the state equation. The activation functions are assumed to beglobally Lipschitz continuous. Based on an appropriate Lyapunov-Krasovskiifunctional, global robust delay-dependent stability criterion which is dependenton both the lower bound and upper bound of the interval time-varying delays isderived by introducing some slack matrix variables. A sufficient condition forthe discrete stochastic recurrent neural networks with interval time-varyingdelays is presented in terms of the linear matrix inequality (LMI). A Numericalexample is given to demonstrate the reduced conservatism of the proposed resultsin this paper.
Relation: ICIC Express Letters, 3(3): 457-463
Appears in Collections:[工業教育與技術學系] 期刊論文

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