Split-and-Combine Singular Value Decomposition for Large-Scale Matrix
The singular value decomposition (SVD) is a fundamental matrix decomposition in linear algebra. It is widely applied in many modern techniques, for example, high- dimensional data visualization, dimension reduction, data mining, latent semantic analysis, and so forth. Although the SVD plays an essen...
| मुख्य लेखक: | |
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| स्वरूप: | लेख |
| भाषा: | English |
| प्रकाशित: |
Wiley
2013-01-01
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| श्रृंखला: | Journal of Applied Mathematics |
| ऑनलाइन पहुंच: | http://dx.doi.org/10.1155/2013/683053 |