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arXiv 2109.09218math.ATcs.CGcs.NAmath.NA
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Betti序列对持久同调的不稳定性及Betti序列的稳定化

Instability of the Betti Sequence for Persistent Homology and a Stabilized Version of the Betti Sequence

Megan Johnson, Jae-Hun Jung

摘要:

拓扑数据分析(TDA)是一个相对较新的数据分析领域,已被证明在各种应用中非常有用。TDA的主要持久化工具是持久化同源性,其中在许多尺度上检查数据结构。持久同源性的表示包括持久性条形码和持久性图,这两者都不容易与传统的机器学习算法相协调,因为它们是间隔集或多集。忠实地表示条形码和持久图的问题一直沿着两个主要途径进行:内核方法和矢量化。一种矢量化是从持久性条形码导出的Betti序列或Betti曲线。虽然贝蒂序列已被用于各种应用中的分类问题,但据我们所知,序列的稳定性以前从未被讨论过。在本文中,我们表明,贝蒂序列是不稳定的1-Wasserstein度量方面的小扰动的条形码从它的计算。此外,我们提出了一种新的稳定版本的贝蒂序列的基础上看到的高斯平滑的稳定持久性袋字持久同源性。然后,我们介绍了规范化的累积贝蒂序列,并提供数值例子,支持的主要声明的文件。

英文摘要:

Topological Data Analysis (TDA), a relatively new field of data analysis, has proved very useful in a variety of applications. The main persistence tool from TDA is persistent homology in which data structure is examined at many scales. Representations of persistent homology include persistence barcodes and persistence diagrams, both of which are not straightforward to reconcile with traditional machine learning algorithms as they are sets of intervals or multisets. The problem of faithfully representing barcodes and persistent diagrams has been pursued along two main avenues: kernel methods and vectorizations. One vectorization is the Betti sequence, or Betti curve, derived from the persistence barcode. While the Betti sequence has been used in classification problems in various applications, to our knowledge, the stability of the sequence has never before been discussed. In this paper we show that the Betti sequence is unstable under the 1-Wasserstein metric with regards to small perturbations in the barcode from which it is calculated. In addition, we propose a novel stabilized version of the Betti sequence based on the Gaussian smoothing seen in the Stable Persistence Bag of Words for persistent homology. We then introduce the normalized cumulative Betti sequence and provide numerical examples that support the main statement of the paper.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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