Improved criteria on delay-dependent stability for discrete-time neural networks with interval time-varying delays

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

doi:10.1155/2012/285931

Improved criteria on delay-dependent stability for discrete-time neural networks with interval time-varying delays

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

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2 Scopus citations

Abstract

The purpose of this paper is to investigate the delay-dependent stability analysis for discrete-time neural networks with interval time-varying delays. Based on Lyapunov method, improved delay-dependent criteria for the stability of the networks are derived in terms of linear matrix inequalities (LMIs) by constructing a suitable Lyapunov-Krasovskii functional and utilizing reciprocally convex approach. Also, a new activation condition which has not been considered in the literature is proposed and utilized for derivation of stability criteria. Two numerical examples are given to illustrate the effectiveness of the proposed method.

Original language	English
Article number	285931
Journal	Abstract and Applied Analysis
Volume	2012
DOIs	https://doi.org/10.1155/2012/285931
State	Published - 2012

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abstract = "The purpose of this paper is to investigate the delay-dependent stability analysis for discrete-time neural networks with interval time-varying delays. Based on Lyapunov method, improved delay-dependent criteria for the stability of the networks are derived in terms of linear matrix inequalities (LMIs) by constructing a suitable Lyapunov-Krasovskii functional and utilizing reciprocally convex approach. Also, a new activation condition which has not been considered in the literature is proposed and utilized for derivation of stability criteria. Two numerical examples are given to illustrate the effectiveness of the proposed method.",

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

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AU - Park, M. J.

AU - Park, Ju H.

AU - Lee, S. M.

AU - Cha, E. J.

PY - 2012

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N2 - The purpose of this paper is to investigate the delay-dependent stability analysis for discrete-time neural networks with interval time-varying delays. Based on Lyapunov method, improved delay-dependent criteria for the stability of the networks are derived in terms of linear matrix inequalities (LMIs) by constructing a suitable Lyapunov-Krasovskii functional and utilizing reciprocally convex approach. Also, a new activation condition which has not been considered in the literature is proposed and utilized for derivation of stability criteria. Two numerical examples are given to illustrate the effectiveness of the proposed method.

AB - The purpose of this paper is to investigate the delay-dependent stability analysis for discrete-time neural networks with interval time-varying delays. Based on Lyapunov method, improved delay-dependent criteria for the stability of the networks are derived in terms of linear matrix inequalities (LMIs) by constructing a suitable Lyapunov-Krasovskii functional and utilizing reciprocally convex approach. Also, a new activation condition which has not been considered in the literature is proposed and utilized for derivation of stability criteria. Two numerical examples are given to illustrate the effectiveness of the proposed method.

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DO - 10.1155/2012/285931

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VL - 2012

JO - Abstract and Applied Analysis

JF - Abstract and Applied Analysis

M1 - 285931

ER -

Improved criteria on delay-dependent stability for discrete-time neural networks with interval time-varying delays

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