Part II Numerical Mathematics

BIT Numerical Mathematics

, Volume 27, Issue 4, pp 534-553

First online:

The truncatedSVD as a method for regularization

  • Per Christian HansenAffiliated withCopenhagen University Observatory

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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.

AMS subject classification

65F20 65F30


truncated SVD regularization in standard form perturbation theory for truncated SVD numerical rank