Delay-dependent approach to robust stability for uncertain discretestochastic recurrent neural networks with interval time-varying delays

被引：0

作者：

Lu, Chien-Yu ^{[1
]}

Shyr, Wen-Jye ^{[1
]}

Yao, Kai-Chao ^{[1
]}

Chen, Der-Fa ^{[1
]}

机构：

[1] Department of Industrial Education and Technology, National Changhua University of Education, No. 1, Jin-De Road, Changhua 500, Taiwan

来源：

ICIC Express Letters | 2009年 / 3卷 / 03期

关键词：

Time delay - Time varying networks - Equations of state - Time varying control systems - Recurrent neural networks - Robustness (control systems) - Stability criteria - Stochastic systems;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

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. ICIC International © 2009.

引用

页码：457 / 463

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