铁矿烧结矿三维体素数据的非负矩阵分解持续同源性分析

IF 0.4 Q4 MATHEMATICS, APPLIED

JSIAM Letters Pub Date : 2022-08-25 DOI:10.14495/jsiaml.14.151

I. Obayashi, M. Kimura

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引用次数: 1

摘要

本文提出了一种基于持续同调和非负矩阵分解的数据分析方法。使用连接持久化图像技术从隐藏在数据后面的不同维的持久化图中提取共存结构。为了证明该方法的潜力，我们将该方法应用于通过x射线计算机断层扫描获得的铁矿石烧结体的三维体素数据。分析成功地捕获了这些铁矿烧结矿中的共存结构。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Persistent homology analysis with nonnegative matrix factorization for 3D voxel data of iron ore sinters

This paper proposes a data analysis method using persistent homology and nonnegative matrix factorization. A concatenated persistence image technique is used to extract coexisting structures from the persistence diagrams of different dimensions hidden behind the data. To demonstrate the potential of our method, we apply the method to 3D voxel data of iron ore sinters obtained by X-ray computed tomography. The analysis successfully captures the coexistence structures in these iron ore sinters.

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来源期刊

JSIAM Letters MATHEMATICS, APPLIED-

自引率

25.00%

发文量