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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/13659

Title: An LMI approach to passivity analysis for uncertain neural networks with multiple time-varying delays
Authors: Lu, Chien-Yu;Liao, Chin-Wen;Tsai, Hsun-Heng;Tsai, Jason Sheng-Hong;Cheng, Jui-Chuan
Contributors: 工業教育與技術學系
Keywords: Passivity conditions;Linear matrix inequality;Neural networks;Uncertainty
Date: 2007-03
Issue Date: 2012-08-27T10:40:32Z
Abstract: This paper deals with the problem of Passivity analysis for neural networks with multiple time-varying delays subject to norm-bounded time-varying parameter uncertainties. The activation functions are supposed to be bounded and globally Lipschitz continuous. New passivity conditions are proposed by using Lyapunov-Krasovskii functionals and the free–weighting matrix method to relax the existing requirement of derivative
of time delays of the system. Passivity conditions are obtained in terms of linear matrix inequalities, which can be investigated easily by using recently developed standard algorithms. Two illustrative examples are provided to demonstrate the effectiveness.
Relation: International Journal of Electrical Engineering, 14: 307-314
Appears in Collections:[Department of Industrial Education and Technology] Periodical Articles

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