The truncatedSVD as a method for regularization
- Per Christian Hansen
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The truncated singular value decomposition (SVD) is considered as a method for regularization of ill-posed linear least squares problems. In particular, the truncated SVD solution is compared with the usual regularized solution. Necessary conditions are defined in which the two methods will yield similar results. This investigation suggests the truncated SVD as a favorable alternative to standard-form regularization in cases of ill-conditioned matrices with well-determined numerical rank.
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- The truncatedSVD as a method for regularization
BIT Numerical Mathematics
Volume 27, Issue 4 , pp 534-553
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers
- Additional Links
- truncated SVD
- regularization in standard form
- perturbation theory for truncated SVD
- numerical rank
- Industry Sectors
- Author Affiliations
- 1. Copenhagen University Observatory, Øster Voldgade 3, DK-1350, København K, Denmark