Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays

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 (LM...

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Main Authors: O. M. Kwon, M. J. Park, Ju H. Park, S. M. Lee, E. J. Cha
Format: Article
Language:English
Published: Wiley 2012-01-01
Series:Abstract and Applied Analysis
Online Access:http://dx.doi.org/10.1155/2012/285931
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author O. M. Kwon
M. J. Park
Ju H. Park
S. M. Lee
E. J. Cha
author_facet O. M. Kwon
M. J. Park
Ju H. Park
S. M. Lee
E. J. Cha
author_sort O. M. Kwon
collection DOAJ
description 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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institution Kabale University
issn 1085-3375
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language English
publishDate 2012-01-01
publisher Wiley
record_format Article
series Abstract and Applied Analysis
spelling doaj-art-21b42f2fd37a4d718359832b2135b32c2025-08-20T03:54:42ZengWileyAbstract and Applied Analysis1085-33751687-04092012-01-01201210.1155/2012/285931285931Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying DelaysO. M. Kwon0M. J. Park1Ju H. Park2S. M. Lee3E. J. Cha4School of Electrical Engineering, Chungbuk National University, 52 Naesudong-ro, Heungduk-gu, Cheongju 361-763, Republic of KoreaSchool of Electrical Engineering, Chungbuk National University, 52 Naesudong-ro, Heungduk-gu, Cheongju 361-763, Republic of KoreaDepartment of Electrical Engineering, Yeungnam University, 214-1 Dae-Dong, Gyeongsan 712-749, Republic of KoreaSchool of Electronic Engineering, Daegu University, Gyeongsan 712-714, Republic of KoreaDepartment of Biomedical Engineering, School of Medicine, Chungbuk National University, 52 Naesudong-ro, Heungduk-gu, Cheongju 361-763, Republic of KoreaThe 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.http://dx.doi.org/10.1155/2012/285931
spellingShingle O. M. Kwon
M. J. Park
Ju H. Park
S. M. Lee
E. J. Cha
Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays
Abstract and Applied Analysis
title Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays
title_full Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays
title_fullStr Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays
title_full_unstemmed Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays
title_short Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays
title_sort improved criteria on delay dependent stability for discrete time neural networks with interval time varying delays
url http://dx.doi.org/10.1155/2012/285931
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