Passivity analysis for Markovian jumping neutral type neural networks with leakage and mode-dependent delay

IF 1.1 Q4 BIOPHYSICS AIMS Biophysics Pub Date : 2023-01-01 DOI:10.3934/biophy.2023012
N. Mala, Arumugam Vinodkumar, J. Alzabut
{"title":"Passivity analysis for Markovian jumping neutral type neural networks with leakage and mode-dependent delay","authors":"N. Mala, Arumugam Vinodkumar, J. Alzabut","doi":"10.3934/biophy.2023012","DOIUrl":null,"url":null,"abstract":"In this study, we discuss the passivity analysis for Markovian jumping Neural Networks of neural-type. The results are demonstrated using phases of linear matrix inequalities as well as an improved Lyapunov-Krasovskii functional (LKF) of the triple integral terms and quadruple integrals. The information of the mode-dependent of all delays have been taken into account in the constructed Lyapunov–Krasovskii functional and novel stability criterion is derived. The value of selecting as many Lyapunov matrices that are mode-dependent as possible is demonstrated. The effectiveness and decreased conservatism of the aforementioned theoretical results are eventually demonstrated by a numerical example.","PeriodicalId":7529,"journal":{"name":"AIMS Biophysics","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AIMS Biophysics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3934/biophy.2023012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOPHYSICS","Score":null,"Total":0}
引用次数: 1

Abstract

In this study, we discuss the passivity analysis for Markovian jumping Neural Networks of neural-type. The results are demonstrated using phases of linear matrix inequalities as well as an improved Lyapunov-Krasovskii functional (LKF) of the triple integral terms and quadruple integrals. The information of the mode-dependent of all delays have been taken into account in the constructed Lyapunov–Krasovskii functional and novel stability criterion is derived. The value of selecting as many Lyapunov matrices that are mode-dependent as possible is demonstrated. The effectiveness and decreased conservatism of the aforementioned theoretical results are eventually demonstrated by a numerical example.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
具有泄漏和模相关延迟的马尔可夫跳变中立型神经网络的无源性分析
本文讨论了神经型马尔可夫跳变神经网络的无源性分析。利用线性矩阵不等式的相位以及三重积分项和四重积分项的改进Lyapunov-Krasovskii泛函(LKF)证明了结果。在构造的Lyapunov-Krasovskii泛函中考虑了所有时滞的模态相关信息,导出了新的稳定性判据。选择尽可能多的李雅普诺夫矩阵的价值是模相关的证明。最后通过数值算例证明了上述理论结果的有效性和降低了保守性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
AIMS Biophysics
AIMS Biophysics BIOPHYSICS-
CiteScore
2.40
自引率
20.00%
发文量
16
审稿时长
8 weeks
期刊介绍: AIMS Biophysics is an international Open Access journal devoted to publishing peer-reviewed, high quality, original papers in the field of biophysics. We publish the following article types: original research articles, reviews, editorials, letters, and conference reports. AIMS Biophysics welcomes, but not limited to, the papers from the following topics: · Structural biology · Biophysical technology · Bioenergetics · Membrane biophysics · Cellular Biophysics · Electrophysiology · Neuro-Biophysics · Biomechanics · Systems biology
期刊最新文献
Endoplasmic reticulum localization of phosphoinositide specific phospholipase C enzymes in U73122 cultured human osteoblasts Identification of potential SARS-CoV-2 papain-like protease inhibitors with the ability to interact with the catalytic triad Predicting factors and top gene identification for survival data of breast cancer A review of molecular biology detection methods for human adenovirus Natural bond orbital analysis of dication magnesium complexes [Mg(H2O)6]2+ and [[Mg(H2O)6](H2O)n]2+; n=1-4
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1