Topological data analysis and cosheaves

被引：0
|
作者：
Justin Michael Curry
机构：
[1] Duke University,Department of Mathematics
来源：
Japan Journal of Industrial and Applied Mathematics | 2015年 / 32卷
关键词：
Topological data analysis; Persistent homology; Sheaves and cosheaves; Barcodes; o-minimal topology; 55U99; 46M20; 32S60; 16G20; 62-07; 03C64;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper contains an expository account of persistent homology and its usefulness for topological data analysis. An alternative foundation for level set persistence is presented using sheaves and cosheaves.
引用
收藏
页码：333 / 371
页数：38
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