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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/13677

Title: A delay-dependent approach to robust stability for uncertain hybrid bidirectional associative memory neural networks with time-varying delays
Authors: Lu, Chien-Yu;Chang, K. Y.;Tsai, H. H.;Chang, W. J.
Contributors: 工業教育與技術學系
Keywords: Time-varying delays;Linear matrix inequality;Bidirectional associative memory neural networks;Parameter uncertainty;Robust stability
Date: 2010
Issue Date: 2012-08-27T10:42:49Z
Abstract: This paper performs a global robust stability analysis of a particular class of hybrid bidirectional associative memory time-varying delayed neural network with norm-bounded timevarying parameter uncertainties. The activation functions are assumed to be globally Lipschitz continuous. Globally delay- dependent robust stability criteria are derived in the form of linear matrix inequalities by introducing relaxation matrices which, when chosen properly, produce a less conservative result. Two numerical examples are given to illustrate the significant improvement obtained in the conservativeness of the delay bound.
Relation: J. Marine Science and Technology, 18(2): 164-171
Appears in Collections:[Department of Industrial Education and Technology] Periodical Articles

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