| Item type |
Trans(1) |
| 公開日 |
2026-01-27 |
| タイトル |
|
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言語 |
ja |
|
タイトル |
Implementation of the OQDS method with a new shift strategy for Principal Component Analysis |
| タイトル |
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言語 |
en |
|
タイトル |
Implementation of the OQDS method with a new shift strategy for Principal Component Analysis |
| 言語 |
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|
言語 |
eng |
| キーワード |
|
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主題Scheme |
Other |
|
主題 |
[オリジナル論文] principal component analysis, partial singular value decomposition, orthogonal QD with shift method |
| 資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
| 著者所属 |
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Graduate School of Humanities and Sciences, Nara Women's University／Presntly ewith Shiga University |
| 著者所属 |
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Research Group of Information and Communication Technology for Life, Nara Women's University |
| 著者所属 |
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Fukui University |
| 著者所属 |
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Osaka Seikei University |
| 著者所属(英) |
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en |
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Graduate School of Humanities and Sciences, Nara Women's University / Presntly ewith Shiga University |
| 著者所属(英) |
|
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|
en |
|
|
Research Group of Information and Communication Technology for Life, Nara Women's University |
| 著者所属(英) |
|
|
|
en |
|
|
Fukui University |
| 著者所属(英) |
|
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|
en |
|
|
Osaka Seikei University |
| 著者名 |
Miho,Chiyonobu
Masami,Takata
Kinji,Kimura
Yoshimasa,Nakamura
|
| 著者名(英) |
Miho Chiyonobu
Masami Takata
Kinji Kimura
Yoshimasa Nakamura
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| 論文抄録 |
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内容記述タイプ |
Other |
|
内容記述 |
This study proposes a method for computing partial singular values and the corresponding singular vectors. Principal component analysis (PCA) requires only a few singular values and the corresponding singular vectors. General partial singular value decomposition employs a combination of bisection and inverse iteration methods. However, this method may be unreliable because of the matrices that reduce the calculation accuracy. Consequently, this study employs the orthogonal QD with shift (OQDS) method. The OQDS method can compute singular values from smaller values and the corresponding right-singular vectors with high accuracy to the lower bi-diagonal matrix if the matrix is not split during computation. Under the split, it is unclear which side of the split the smaller singular values fall. Therefore, addressing this split is necessary for adopting the OQDS method for PCA. In this paper, we propose a new implementation of the OQDS method that is unaffected by splits. Our experimental results confirm that this method exhibits fast performance while maintaining reliability. |
| 論文抄録(英) |
|
|
内容記述タイプ |
Other |
|
内容記述 |
This study proposes a method for computing partial singular values and the corresponding singular vectors. Principal component analysis (PCA) requires only a few singular values and the corresponding singular vectors. General partial singular value decomposition employs a combination of bisection and inverse iteration methods. However, this method may be unreliable because of the matrices that reduce the calculation accuracy. Consequently, this study employs the orthogonal QD with shift (OQDS) method. The OQDS method can compute singular values from smaller values and the corresponding right-singular vectors with high accuracy to the lower bi-diagonal matrix if the matrix is not split during computation. Under the split, it is unclear which side of the split the smaller singular values fall. Therefore, addressing this split is necessary for adopting the OQDS method for PCA. In this paper, we propose a new implementation of the OQDS method that is unaffected by splits. Our experimental results confirm that this method exhibits fast performance while maintaining reliability. |
| 書誌レコードID |
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収録物識別子タイプ |
NCID |
|
収録物識別子 |
AA11464803 |
| 書誌情報 |
情報処理学会論文誌数理モデル化と応用（TOM）
巻 19,
号 1,
p. 1-13,
発行日 2026-01-27
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| ISSN |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
1882-7780 |
| 出版者 |
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言語 |
ja |
|
出版者 |
情報処理学会 |
IPSJ-TOM1901002.pdf (1.2 MB)
