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Status已发表Published
TitleStability Analysis for Delayed Neural Networks via a Novel Negative-Definiteness Determination Method
Creator
Date Issued2022
Source PublicationIEEE Transactions on Cybernetics
ISSN2168-2267
Volume52Issue:6Pages:5356 - 5366
Abstract

The stability of neural networks with a time-varying delay is studied in this article. First, a relaxed Lyapunov-Krasovskii functional (LKF) is presented, in which the positive-definiteness requirement of the augmented quadratic term and the delay-product-type terms are set free, and two double integral states are augmented into the single integral terms at the same time. Second, a new negative-definiteness determination method is put forward for quadratic functions by utilizing Taylor's formula and the interval-decomposition approach. This method encompasses the previous negative-definiteness determination approaches and has less conservatism. Finally, the proposed LKF and the negative-definiteness determination method are applied to the stability analysis of neural networks with a time-varying delay, whose advantages are shown by two numerical examples.

KeywordLyapunov-Krasovskii functional (LKF) negative-definiteness determination method neural networks stability time delay
DOI10.1109/TCYB.2020.3031087
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000819019200118
Scopus ID2-s2.0-85097145564
Citation statistics
Cited Times:43[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/1112
CollectionFaculty of Science and Technology
Corresponding AuthorZhang, Chuanke
Affiliation
1.School of Automation, China University of Geosciences, Wuhan 430074, China
2.Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, China University of Geosciences, Wuhan 430074, China
3.Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education, China University of Geosciences, Wuhan 430074, China
4.BNU-UIC Institute of Artificial Intelligence and Future Networks, Beijing Normal University (BNU Zhuhai), BNU-HKBU United International College, Zhuhai 519087, China.
Recommended Citation
GB/T 7714
Long, Fei,Zhang, Chuanke,He, Yonget al. Stability Analysis for Delayed Neural Networks via a Novel Negative-Definiteness Determination Method[J]. IEEE Transactions on Cybernetics, 2022, 52(6): 5356 - 5366.
APA Long, Fei, Zhang, Chuanke, He, Yong, Wang, Qingguo, & Wu, Min. (2022). Stability Analysis for Delayed Neural Networks via a Novel Negative-Definiteness Determination Method. IEEE Transactions on Cybernetics, 52(6), 5356 - 5366.
MLA Long, Fei,et al."Stability Analysis for Delayed Neural Networks via a Novel Negative-Definiteness Determination Method". IEEE Transactions on Cybernetics 52.6(2022): 5356 - 5366.
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