Inequalities and pth moment exponential stability of impulsive delayed Hopfield neural networks
Abstract In this paper, the pth moment exponential stability for a class of impulsive delayed Hopfield neural networks is investigated. Some concise algebraic criteria are provided by a new method concerned with impulsive integral inequalities. Our discussion neither requires a complicated Lyapunov...
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2021-06-01
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Online Access: | https://doi.org/10.1186/s13660-021-02640-9 |
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doaj-b49898b0808d4ad4a0564c02537030b32021-07-04T11:37:26ZengSpringerOpenJournal of Inequalities and Applications1029-242X2021-06-012021111310.1186/s13660-021-02640-9Inequalities and pth moment exponential stability of impulsive delayed Hopfield neural networksYutian Zhang0Guici Chen1Qi Luo2School of Mathematics & Statistics, Nanjing University of Information Science & TechnologyHubei Province Key Laboratory of System Science in Metallurgical Process, Wuhan University of Science & TechnologySchool of Information & Control, Nanjing University of Information Science & TechnologyAbstract In this paper, the pth moment exponential stability for a class of impulsive delayed Hopfield neural networks is investigated. Some concise algebraic criteria are provided by a new method concerned with impulsive integral inequalities. Our discussion neither requires a complicated Lyapunov function nor the differentiability of the delay function. In addition, we also summarize a new result on the exponential stability of a class of impulsive integral inequalities. Finally, one example is given to illustrate the effectiveness of the obtained results.https://doi.org/10.1186/s13660-021-02640-9pth moment exponential stabilityIntegral inequalityImpulseHopfield neural networksDelay |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yutian Zhang Guici Chen Qi Luo |
spellingShingle |
Yutian Zhang Guici Chen Qi Luo Inequalities and pth moment exponential stability of impulsive delayed Hopfield neural networks Journal of Inequalities and Applications pth moment exponential stability Integral inequality Impulse Hopfield neural networks Delay |
author_facet |
Yutian Zhang Guici Chen Qi Luo |
author_sort |
Yutian Zhang |
title |
Inequalities and pth moment exponential stability of impulsive delayed Hopfield neural networks |
title_short |
Inequalities and pth moment exponential stability of impulsive delayed Hopfield neural networks |
title_full |
Inequalities and pth moment exponential stability of impulsive delayed Hopfield neural networks |
title_fullStr |
Inequalities and pth moment exponential stability of impulsive delayed Hopfield neural networks |
title_full_unstemmed |
Inequalities and pth moment exponential stability of impulsive delayed Hopfield neural networks |
title_sort |
inequalities and pth moment exponential stability of impulsive delayed hopfield neural networks |
publisher |
SpringerOpen |
series |
Journal of Inequalities and Applications |
issn |
1029-242X |
publishDate |
2021-06-01 |
description |
Abstract In this paper, the pth moment exponential stability for a class of impulsive delayed Hopfield neural networks is investigated. Some concise algebraic criteria are provided by a new method concerned with impulsive integral inequalities. Our discussion neither requires a complicated Lyapunov function nor the differentiability of the delay function. In addition, we also summarize a new result on the exponential stability of a class of impulsive integral inequalities. Finally, one example is given to illustrate the effectiveness of the obtained results. |
topic |
pth moment exponential stability Integral inequality Impulse Hopfield neural networks Delay |
url |
https://doi.org/10.1186/s13660-021-02640-9 |
work_keys_str_mv |
AT yutianzhang inequalitiesandpthmomentexponentialstabilityofimpulsivedelayedhopfieldneuralnetworks AT guicichen inequalitiesandpthmomentexponentialstabilityofimpulsivedelayedhopfieldneuralnetworks AT qiluo inequalitiesandpthmomentexponentialstabilityofimpulsivedelayedhopfieldneuralnetworks |
_version_ |
1721320121937428480 |