The truncatedSVD as a method for regularization

  title={The truncatedSVD as a method for regularization},
  author={Per Christian Hansen},
  journal={BIT Numerical Mathematics},
  • P. Hansen
  • Published 1987
  • Mathematics
  • BIT Numerical Mathematics
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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