AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home AIMS Mathematics Article
PDF (247.8 KB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Global attractive periodic solutions of neutral-type neural networks with delays in the leakage terms

Shihong Zhu1, Bo Du2( )
College of Mathematics and Computer, Tongling University, Tongling, Anhui, 244061, China
School of Mathematics and Statistics, Huaiyin Normal University, Huaian, Jiangsu, 223300, China
Show Author Information

Abstract

In this paper, we introduce a class of neutral-type neural networks with delay in the leakage terms. Using coincidence degree theory, Lyapunov functional method and the properties of neutral operator, we establish some new sufficient criteria for the existence and global attractiveness of periodic solutions. Finally, an example demonstrates our findings.

Keywords

periodic solutionneural networksneutral-typeleakage terms
CLC number: 34D23, 92B20

References

【1】
【1】
 
 
Crossref Google Scholar
AIMS Mathematics
Volume 8 Issue 11,
November 2023
Pages 26731-26744
DOI: 10.3934/math.20231368

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Cite this Report
Close
Close
Cite this article:
Zhu S, Du B. Global attractive periodic solutions of neutral-type neural networks with delays in the leakage terms. AIMS Mathematics, 2023, 8(11): 26731-26744. https://doi.org/10.3934/math.20231368

35

Views

1

Downloads

0

Crossref

0

Web of Science

0

Scopus
Received: 09 August 2023
Revised: 06 September 2023
Accepted: 10 September 2023
Published: 15 November 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)