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Soft Computing
Erschienen in: Soft Computing 11/2013

01.11.2013 | Focus

New delay-dependent stability criteria for cohen-grossberg neural networks with multiple time-varying mixed delays

verfasst von: Qihe Shan, Huaguang Zhang, Feisheng Yang, Zhanshan Wang

Erschienen in: Soft Computing | Ausgabe 11/2013

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Abstract

This paper investigates the globally asymptotical stability problem for a general class of Cohen-Grossberg neural networks with multiple mixed time-delays. Before proving the main theorem, a more generalized convex combination inequality is proposed. A new stability criterion for Cohen-Grossberg neural networks with multiple time-varying delays is obtained by the employed general inequality technique. Two examples are included to illustrate the effectiveness of the presented results.
Vorheriger Artikel Passivity analysis for delayed discontinuous neural networks
Nächster Artikel Direct adaptive type-2 fuzzy neural network control for a generic hypersonic flight vehicle

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Metadaten
Titel
New delay-dependent stability criteria for cohen-grossberg neural networks with multiple time-varying mixed delays
verfasst von
Qihe Shan
Huaguang Zhang
Feisheng Yang
Zhanshan Wang
Publikationsdatum
01.11.2013
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 11/2013
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-013-1114-7

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