具有分段交互函数和处理延迟的广义Motsch-Tadmor模型的群集分析

Pub Date : 2022-06-14 DOI:10.21136/AM.2022.0219-21
Yipeng Chen, Yicheng Liu, Xiao Wang
{"title":"具有分段交互函数和处理延迟的广义Motsch-Tadmor模型的群集分析","authors":"Yipeng Chen,&nbsp;Yicheng Liu,&nbsp;Xiao Wang","doi":"10.21136/AM.2022.0219-21","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, a generalized Motsch-Tadmor model with piecewise interaction functions and fixed processing delays is investigated. According to functional differential equation theory and correlation properties of the stochastic matrix, we obtained sufficient conditions for the system achieving flocking, including an upper bound of the time delay parameter. When the parameter is less than the upper bound, the system achieves asymptotic flocking under appropriate assumptions.</p></div>","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.21136/AM.2022.0219-21.pdf","citationCount":"0","resultStr":"{\"title\":\"Flocking analysis for a generalized Motsch-Tadmor model with piecewise interaction functions and processing delays\",\"authors\":\"Yipeng Chen,&nbsp;Yicheng Liu,&nbsp;Xiao Wang\",\"doi\":\"10.21136/AM.2022.0219-21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this paper, a generalized Motsch-Tadmor model with piecewise interaction functions and fixed processing delays is investigated. According to functional differential equation theory and correlation properties of the stochastic matrix, we obtained sufficient conditions for the system achieving flocking, including an upper bound of the time delay parameter. When the parameter is less than the upper bound, the system achieves asymptotic flocking under appropriate assumptions.</p></div>\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2022-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.21136/AM.2022.0219-21.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://link.springer.com/article/10.21136/AM.2022.0219-21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"100","ListUrlMain":"https://link.springer.com/article/10.21136/AM.2022.0219-21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文研究了具有分段相互作用函数和固定处理延迟的广义Motsch-Tamor模型。根据泛函微分方程理论和随机矩阵的相关性质,得到了系统实现聚类的充分条件,包括时滞参数的上界。当参数小于上限时,系统在适当的假设下实现渐近聚类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
分享
查看原文
Flocking analysis for a generalized Motsch-Tadmor model with piecewise interaction functions and processing delays

In this paper, a generalized Motsch-Tadmor model with piecewise interaction functions and fixed processing delays is investigated. According to functional differential equation theory and correlation properties of the stochastic matrix, we obtained sufficient conditions for the system achieving flocking, including an upper bound of the time delay parameter. When the parameter is less than the upper bound, the system achieves asymptotic flocking under appropriate assumptions.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信