Global μ-Stability of Impulsive Complex-Valued Neural Networks with Leakage Delay and Mixed Delays
The impulsive complex-valued neural networks with three kinds of time delays including leakage delay, discrete delay, and distributed delay are considered. Based on the homeomorphism mapping principle of complex domain, a sufficient condition for the existence and uniqueness of the equilibrium point...
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Online Access: | http://dx.doi.org/10.1155/2014/397532 |
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doaj-dee54fabbddf4ceaa7daf926f963b3eb2020-11-24T21:12:34ZengHindawi LimitedAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/397532397532Global μ-Stability of Impulsive Complex-Valued Neural Networks with Leakage Delay and Mixed DelaysXiaofeng Chen0Qiankun Song1Yurong Liu2Zhenjiang Zhao3Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, ChinaDepartment of Mathematics, Chongqing Jiaotong University, Chongqing 400074, ChinaDepartment of Mathematics, Yangzhou University, Yangzhou 225002, ChinaDepartment of Mathematics, Huzhou Teachers College, Huzhou 313000, ChinaThe impulsive complex-valued neural networks with three kinds of time delays including leakage delay, discrete delay, and distributed delay are considered. Based on the homeomorphism mapping principle of complex domain, a sufficient condition for the existence and uniqueness of the equilibrium point of the addressed complex-valued neural networks is proposed in terms of linear matrix inequality (LMI). By constructing appropriate Lyapunov-Krasovskii functionals, and employing the free weighting matrix method, several delay-dependent criteria for checking the global μ-stability of the complex-valued neural networks are established in LMIs. As direct applications of these results, several criteria on the exponential stability, power-stability, and log-stability are obtained. Two examples with simulations are provided to demonstrate the effectiveness of the proposed criteria.http://dx.doi.org/10.1155/2014/397532 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiaofeng Chen Qiankun Song Yurong Liu Zhenjiang Zhao |
spellingShingle |
Xiaofeng Chen Qiankun Song Yurong Liu Zhenjiang Zhao Global μ-Stability of Impulsive Complex-Valued Neural Networks with Leakage Delay and Mixed Delays Abstract and Applied Analysis |
author_facet |
Xiaofeng Chen Qiankun Song Yurong Liu Zhenjiang Zhao |
author_sort |
Xiaofeng Chen |
title |
Global μ-Stability of Impulsive Complex-Valued Neural Networks with Leakage Delay and Mixed Delays |
title_short |
Global μ-Stability of Impulsive Complex-Valued Neural Networks with Leakage Delay and Mixed Delays |
title_full |
Global μ-Stability of Impulsive Complex-Valued Neural Networks with Leakage Delay and Mixed Delays |
title_fullStr |
Global μ-Stability of Impulsive Complex-Valued Neural Networks with Leakage Delay and Mixed Delays |
title_full_unstemmed |
Global μ-Stability of Impulsive Complex-Valued Neural Networks with Leakage Delay and Mixed Delays |
title_sort |
global μ-stability of impulsive complex-valued neural networks with leakage delay and mixed delays |
publisher |
Hindawi Limited |
series |
Abstract and Applied Analysis |
issn |
1085-3375 1687-0409 |
publishDate |
2014-01-01 |
description |
The impulsive complex-valued neural networks with three kinds of time delays including leakage delay, discrete delay, and distributed delay are considered. Based on the homeomorphism mapping principle of complex domain, a sufficient condition for the existence and uniqueness of the equilibrium point of the addressed complex-valued neural networks is proposed in terms of linear matrix inequality (LMI). By constructing appropriate Lyapunov-Krasovskii functionals, and employing the free weighting matrix method, several delay-dependent criteria for checking the global μ-stability of the complex-valued neural networks are established in LMIs. As direct applications of these results, several criteria on the exponential stability, power-stability, and log-stability are obtained. Two examples with simulations are provided to demonstrate the effectiveness of the proposed criteria. |
url |
http://dx.doi.org/10.1155/2014/397532 |
work_keys_str_mv |
AT xiaofengchen globalmstabilityofimpulsivecomplexvaluedneuralnetworkswithleakagedelayandmixeddelays AT qiankunsong globalmstabilityofimpulsivecomplexvaluedneuralnetworkswithleakagedelayandmixeddelays AT yurongliu globalmstabilityofimpulsivecomplexvaluedneuralnetworkswithleakagedelayandmixeddelays AT zhenjiangzhao globalmstabilityofimpulsivecomplexvaluedneuralnetworkswithleakagedelayandmixeddelays |
_version_ |
1716750603109007360 |