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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/26510

Title: A DELAY-DEPENDENT APPROACH TO ROBUST STABILITY FOR UNCERTAIN STOCHASTIC NEURAL NETWORKS WITH TIME-VARYING DELAY
Authors: Chien-Yu Lu;Chin-Wen Liao;Koan-Yuh Chang;Wen-Jer Chang
Contributors: 國立臺灣海洋大學:輪機工程學系
Keywords: time-varying delay;linear matrix inequality;neural networks;uncertainty;robust stability
Date: 2010
Issue Date: 2011-10-20T08:36:23Z
Publisher: Journal of Marine Science and Technology
Abstract: Abstract:This paper investigates the global delay-dependent robust stability in the mean square for uncertain stochastic neural networks with time-varying delay. The activation functions are assumed to be globally Lipschitz continuous. Based on a linear matrix inequality approach, globally delay-dependent robust stability criterion is derived by introducing some relaxation matrices which, when chosen properly, lead to a less
conservative result. Two numerical examples are given to illustrate the effectiveness of the method.
Relation: 18(1), pp.77-83
URI: http://ntour.ntou.edu.tw/handle/987654321/26510
Appears in Collections:[輪機工程學系] 期刊論文

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