Fast algorithm of the singular value decomposition
| Project/Area Number |
23860014
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Single-year Grants |
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| Research Field |
Engineering fundamentals
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| Research Institution | The University of Tokyo |
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Principal Investigator |
AISHIMA KENSUKE 東京大学, 情報理工学(系)研究科, 助教 (40609658)
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| Project Period (FY) |
2011-08-24 – 2013-03-31
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2012: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2011: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | 線形計算 |
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| Research Abstract |
Matrix singular value decomposition plays an important role in many application areas. In this study, we have improved the differential quotient difference with shifts (dqds) algorithm, which is one of the most efficient iterative algorithms of bidiagonal SVD. We have incorporated a new aggressive deflation into the dqds. Our algorithm is faster than the original algorithm. Also we showed convergence rates of the dqds. Furthermore, we proposed a new multishift QR algorithm for symmetric eigenvalue problems. We also proved its global convergence.
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Report
(3 results)
Research Products
(16 results)
