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Improved reciprocally convex inequality for stability analysis of neural networks with time-varying delay
Shi, Chenyang1,2; Hoi, Kachon2; Vong, Seakweng2
2023-01-12
Source PublicationNeurocomputing
ISSN0925-2312
Volume527Pages:167-173
Abstract

In this paper, the stability of a type of neural network with time-varying delay is studied. Two general (α,β) and (α,β,γ)-dependent reciprocally convex inequalities with two and three terms are derived to introduce some quadratic terms into the estimate for the derivative of the Lyapunov–Krasovskii functionals (LKFs). The LKF method is used to develop a stability criterion for time-delay neural networks by using the new inequalities. To demonstrate the improvement of the new criterion, numerical results are provided.

KeywordLyapunov–krasovskii Functional Neural Networks Reciprocally Convex Inequality Time-varying Delay
DOI10.1016/j.neucom.2023.01.048
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000922292600001
PublisherELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
Scopus ID2-s2.0-85146729061
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Document TypeJournal article
CollectionDEPARTMENT OF MATHEMATICS
Corresponding AuthorVong, Seakweng
Affiliation1.Department of Mathematics, South China Agricultural University, Guangzhou, China
2.Department of Mathematics, University of Macau, Avenida da Universidade, Macao
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Shi, Chenyang,Hoi, Kachon,Vong, Seakweng. Improved reciprocally convex inequality for stability analysis of neural networks with time-varying delay[J]. Neurocomputing, 2023, 527, 167-173.
APA Shi, Chenyang., Hoi, Kachon., & Vong, Seakweng (2023). Improved reciprocally convex inequality for stability analysis of neural networks with time-varying delay. Neurocomputing, 527, 167-173.
MLA Shi, Chenyang,et al."Improved reciprocally convex inequality for stability analysis of neural networks with time-varying delay".Neurocomputing 527(2023):167-173.
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