Novel delay-dependent asymptotic stability criteria for neural networks with time-varying delays

Junkang Tian; Dongsheng Xu; Jian Zu

doi:10.1016/j.cam.2008.09.002

Novel delay-dependent asymptotic stability criteria for neural networks with time-varying delays

Junkang Tian
, Dongsheng Xu
, Jian Zu

Southwest Petroleum University China

科研成果: 期刊稿件 › 文章 › 同行评审

9 引用（Scopus）

摘要

The problem of delay-dependent asymptotic stability criteria for neural networks (NNs) with time-varying delays is investigated. An improved linear matrix inequality based on delay-dependent stability test is introduced to ensure a large upper bound for time-delay. A new class of Lyapunov function is constructed to derive a novel delay-dependent stability criteria. Finally, numerical examples are given to indicate significant improvement over some existing results.

源语言	英语
页（从-至）	133-138
页数	6
期刊	Journal of Computational and Applied Mathematics
卷	228
期	1
DOI	https://doi.org/10.1016/j.cam.2008.09.002
出版状态	已出版 - 1 6月 2009
已对外发布	是

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abstract = "The problem of delay-dependent asymptotic stability criteria for neural networks (NNs) with time-varying delays is investigated. An improved linear matrix inequality based on delay-dependent stability test is introduced to ensure a large upper bound for time-delay. A new class of Lyapunov function is constructed to derive a novel delay-dependent stability criteria. Finally, numerical examples are given to indicate significant improvement over some existing results.",

keywords = "Delay-dependent, Linear matrix inequality (LMI), Neural networks (NNs), Time-varying delay",

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AU - Xu, Dongsheng

AU - Zu, Jian

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N2 - The problem of delay-dependent asymptotic stability criteria for neural networks (NNs) with time-varying delays is investigated. An improved linear matrix inequality based on delay-dependent stability test is introduced to ensure a large upper bound for time-delay. A new class of Lyapunov function is constructed to derive a novel delay-dependent stability criteria. Finally, numerical examples are given to indicate significant improvement over some existing results.

AB - The problem of delay-dependent asymptotic stability criteria for neural networks (NNs) with time-varying delays is investigated. An improved linear matrix inequality based on delay-dependent stability test is introduced to ensure a large upper bound for time-delay. A new class of Lyapunov function is constructed to derive a novel delay-dependent stability criteria. Finally, numerical examples are given to indicate significant improvement over some existing results.

KW - Delay-dependent

KW - Linear matrix inequality (LMI)

KW - Neural networks (NNs)

KW - Time-varying delay

UR - https://www.scopus.com/pages/publications/63349092338

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DO - 10.1016/j.cam.2008.09.002

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JO - Journal of Computational and Applied Mathematics

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Novel delay-dependent asymptotic stability criteria for neural networks with time-varying delays

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