Global Dissipativity on Uncertain Discrete-Time Neural Networks with Time-Varying Delays

The problems on global dissipativity and global exponential dissipativity are investigated for uncertain discrete-time neural networks with time-varying delays and general activation functions. By constructing appropriate Lyapunov-Krasovskii functionals and employing linear matrix inequality techniq...

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Main Authors: Qiankun Song, Jinde Cao
Format: Article
Language:English
Published: Wiley 2010-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2010/810408
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author Qiankun Song
Jinde Cao
author_facet Qiankun Song
Jinde Cao
author_sort Qiankun Song
collection DOAJ
description The problems on global dissipativity and global exponential dissipativity are investigated for uncertain discrete-time neural networks with time-varying delays and general activation functions. By constructing appropriate Lyapunov-Krasovskii functionals and employing linear matrix inequality technique, several new delay-dependent criteria for checking the global dissipativity and global exponential dissipativity of the addressed neural networks are established in linear matrix inequality (LMI), which can be checked numerically using the effective LMI toolbox in MATLAB. Illustrated examples are given to show the effectiveness of the proposed criteria. It is noteworthy that because neither model transformation nor free-weighting matrices are employed to deal with cross terms in the derivation of the dissipativity criteria, the obtained results are less conservative and more computationally efficient.
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issn 1026-0226
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series Discrete Dynamics in Nature and Society
spelling doaj-art-553c78917fbc4d3eabacc2670cab9b8a2025-08-20T02:05:07ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2010-01-01201010.1155/2010/810408810408Global Dissipativity on Uncertain Discrete-Time Neural Networks with Time-Varying DelaysQiankun Song0Jinde Cao1Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, ChinaDepartment of Mathematics, Southeast University, Nanjing 210096, ChinaThe problems on global dissipativity and global exponential dissipativity are investigated for uncertain discrete-time neural networks with time-varying delays and general activation functions. By constructing appropriate Lyapunov-Krasovskii functionals and employing linear matrix inequality technique, several new delay-dependent criteria for checking the global dissipativity and global exponential dissipativity of the addressed neural networks are established in linear matrix inequality (LMI), which can be checked numerically using the effective LMI toolbox in MATLAB. Illustrated examples are given to show the effectiveness of the proposed criteria. It is noteworthy that because neither model transformation nor free-weighting matrices are employed to deal with cross terms in the derivation of the dissipativity criteria, the obtained results are less conservative and more computationally efficient.http://dx.doi.org/10.1155/2010/810408
spellingShingle Qiankun Song
Jinde Cao
Global Dissipativity on Uncertain Discrete-Time Neural Networks with Time-Varying Delays
Discrete Dynamics in Nature and Society
title Global Dissipativity on Uncertain Discrete-Time Neural Networks with Time-Varying Delays
title_full Global Dissipativity on Uncertain Discrete-Time Neural Networks with Time-Varying Delays
title_fullStr Global Dissipativity on Uncertain Discrete-Time Neural Networks with Time-Varying Delays
title_full_unstemmed Global Dissipativity on Uncertain Discrete-Time Neural Networks with Time-Varying Delays
title_short Global Dissipativity on Uncertain Discrete-Time Neural Networks with Time-Varying Delays
title_sort global dissipativity on uncertain discrete time neural networks with time varying delays
url http://dx.doi.org/10.1155/2010/810408
work_keys_str_mv AT qiankunsong globaldissipativityonuncertaindiscretetimeneuralnetworkswithtimevaryingdelays
AT jindecao globaldissipativityonuncertaindiscretetimeneuralnetworkswithtimevaryingdelays