Journal
JSIAM LETTERS
Volume 14, Issue -, Pages 151-154Publisher
JAPAN SOC INDUSTRIAL & APPLIED MATHEMATICS-JSIAM
DOI: 10.14495/jsiaml.14.151
Keywords
persistent homology; nonnegative matrix factorization; topological data analysis
Categories
Funding
- JSPS KAKENHI [JP 19H00834]
- JSPS [20H05884, 22H05109]
- JST [JPMJPR1923]
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This paper proposes a data analysis method using persistent homology and nonnegative matrix factorization to extract coexisting structures from the persistence diagrams of different dimensions hidden behind the data. The method is successfully applied to 3D voxel data of iron ore sinters obtained by X-ray computed tomography, capturing the coexistence structures in these samples.
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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