Improved approaches to stability criteria for neural networks with time-varying delays

O. M. Kwon; M. J. Park; Ju H. Park; S. M. Lee; E. J. Cha

doi:10.1016/j.jfranklin.2013.06.014

Improved approaches to stability criteria for neural networks with time-varying delays

O. M. Kwon, M. J. Park, Ju H. Park, S. M. Lee, E. J. Cha

School of Electronics Engineering

Research output: Contribution to journal › Article › peer-review

28 Scopus citations

Abstract

Abstract In this paper, the problem of stability analysis for neural networks with time-varying delays is considered. By the use of a newly augmented Lyapunov functional and some novel techniques, sufficient conditions to guarantee the asymptotic stability of the concerned networks are established in terms of linear matrix inequalities (LMIs). Three numerical examples are given to show the improved stability region of the proposed works.

Original language	English
Pages (from-to)	2710-2735
Number of pages	26
Journal	Journal of the Franklin Institute
Volume	350
Issue number	9
DOIs	https://doi.org/10.1016/j.jfranklin.2013.06.014
State	Published - Nov 2013

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10.1016/j.jfranklin.2013.06.014

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title = "Improved approaches to stability criteria for neural networks with time-varying delays",

abstract = "Abstract In this paper, the problem of stability analysis for neural networks with time-varying delays is considered. By the use of a newly augmented Lyapunov functional and some novel techniques, sufficient conditions to guarantee the asymptotic stability of the concerned networks are established in terms of linear matrix inequalities (LMIs). Three numerical examples are given to show the improved stability region of the proposed works.",

author = "Kwon, {O. M.} and Park, {M. J.} and Park, {Ju H.} and Lee, {S. M.} and Cha, {E. J.}",

year = "2013",

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AU - Kwon, O. M.

AU - Park, M. J.

AU - Park, Ju H.

AU - Lee, S. M.

AU - Cha, E. J.

PY - 2013/11

Y1 - 2013/11

N2 - Abstract In this paper, the problem of stability analysis for neural networks with time-varying delays is considered. By the use of a newly augmented Lyapunov functional and some novel techniques, sufficient conditions to guarantee the asymptotic stability of the concerned networks are established in terms of linear matrix inequalities (LMIs). Three numerical examples are given to show the improved stability region of the proposed works.

AB - Abstract In this paper, the problem of stability analysis for neural networks with time-varying delays is considered. By the use of a newly augmented Lyapunov functional and some novel techniques, sufficient conditions to guarantee the asymptotic stability of the concerned networks are established in terms of linear matrix inequalities (LMIs). Three numerical examples are given to show the improved stability region of the proposed works.

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SP - 2710

EP - 2735

JO - Journal of the Franklin Institute

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ER -

Improved approaches to stability criteria for neural networks with time-varying delays

Abstract

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