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NCUEIR > College of Technology > Department of Industrial Education and Technology > Proceedings > Item 987654321/13625

Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/13625

Title:	Delay-Dependent Approach to Robust Stability for Uncertain Discrete Stochastic Recurrent Neural Networks with Interval Time-Varying Delays
Authors:	Lu, Chien-Yu;Zheng, Kai-Yuan;Liao, Chin-Wen
Contributors:	工業教育與技術學系
Keywords:	Discrete stochastic recurrent neural network;Interval time-varying delay;Linear matrix inequality;Uncertainty;Robust stability
Date:	2008-11
Issue Date:	2012-08-27T10:36:04Z
Publisher:	National Cheng Kung University
Abstract:	This paper considers the problem of global robust delay-range-dependent stability for uncertain discrete stochastic recurrent neural networks with interval time-varying delays. The parameter uncertainties are assumed to be time-varying norm-bounded in the state equation. The activation functions are assumed to be globally Lipschitz continuous. Based on an appropriate Lyapunov- Krasovskii functional, global robust delay-dependent stability criterion which is dependent on both the lower bound and upper bound of the interval time-varying delays is derived. A sufficient condition for the discrete stochastic recurrent neural networks with interval time-varying delays is presented in terms of the linear matrix inequality (LMI). An example is given to demonstrate the reduced conservatism of the proposed results in this paper.
Relation:	2008 CACS International Automatic Control Conference, National Cheng Kung University, Tainan, Taiwan, Nov. 21-23, 2008
Appears in Collections:	[Department of Industrial Education and Technology] Proceedings

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