The truncated SVD as a method for regularization Export

@article{citeulike:1397677, abstract = {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.}, author = {Hansen, Per C.}, citeulike-article-id = {1397677}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/BF01937276}, day = {1}, doi = {10.1007/BF01937276}, journal = {BIT Numerical Mathematics}, keywords = {mathematics, matrix, regularisation}, month = {December}, number = {4}, pages = {534--553}, posted-at = {2007-06-19 00:19:12}, priority = {1}, title = {The truncated SVD as a method for regularization}, url = {http://dx.doi.org/10.1007/BF01937276}, volume = {27}, year = {1987} }

TY - JOUR ID - citeulike:1397677 L3 - citeulike-article-id:1397677 N2 - 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. IS - 4 JF - BIT Numerical Mathematics EP - 553 TI - The truncated SVD as a method for regularization VL - 27 SP - 534 KW - mathematics KW - matrix KW - regularisation AU - Hansen, Per PY - 1987/12/01/ UR - http://dx.doi.org/10.1007/BF01937276 ER -