Persistence Terrace for Topological Inference of Point Cloud Data

Persistence Terrace for Topological Inference of Point Cloud Data
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用于点云数据拓扑推理的持久化平台

DOI:
10.1080/10618600.2017.1422432
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发表时间:
2017
影响因子:
2.4
通讯作者:
N. Lazar
N. Lazar
中科院分区:
数学2区
文献类型:
--
作者:
Chul Moon;Noah Giansiracusa;N. Lazar

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拓扑数据分析(TDA)是一种快速发展的用于研究点云和其他数据类型形状的方法。一种流行的方法,旨在对噪声和离群值具有鲁棒性,是首先使用平滑函数将点云转换为流形,然后将持久同源性应用于莫尔斯过滤。一个重大的挑战是,这个平滑过程涉及到一个参数的选择和持久的同源性是高度敏感的选择,此外,重要的尺度信息丢失。我们提出了一种新的拓扑摘要图,称为持久性平台,它采用了广泛的平滑参数,是强大的,多尺度的,无参数。该图允许人们隔离不同的拓扑信号,这些信号可能已经合并为平滑参数的任何固定值,并且它还允许人们推断拓扑特征的大小和点密度。我们在一些简单的设置中说明了我们的方法,其中噪声是现有框架的一个严重问题,然后我们通过计算横截面图像中的肌纤维将其应用于真实的数据集。这篇文章的补充材料可在网上查阅。
ABSTRACT Topological data analysis (TDA) is a rapidly developing collection of methods for studying the shape of point cloud and other data types. One popular approach, designed to be robust to noise and outliers, is to first use a smoothing function to convert the point cloud into a manifold and then apply persistent homology to a Morse filtration. A significant challenge is that this smoothing process involves the choice of a parameter and persistent homology is highly sensitive to that choice; moreover, important scale information is lost. We propose a novel topological summary plot, called a persistence terrace, that incorporates a wide range of smoothing parameters and is robust, multi-scale, and parameter-free. This plot allows one to isolate distinct topological signals that may have merged for any fixed value of the smoothing parameter, and it also allows one to infer the size and point density of the topological features. We illustrate our method in some simple settings where noise is a serious issue for existing frameworks and then we apply it to a real dataset by counting muscle fibers in a cross-sectional image. Supplementary material for this article is available online.
DOI: 10.1214/15-aoas886
发表时间: 2016
期刊: The annals of applied statistics
影响因子: --
作者:
Bendich P;Marron JS;Miller E;Pieloch A;Skwerer S
通讯作者: Skwerer S
DOI: 10.1152/japplphysiol.01022.2012
发表时间: 2013-01-01
影响因子: 3.3
作者:
Mula, Jyothi;Lee, Jonah D.;Peterson, Charlotte A.
通讯作者: Peterson, Charlotte A.