BIB-VERSION:: CS-TR-v2.0
          ID:: STAN//NA-M-86-36
       ENTRY:: January 28, 1996
ORGANIZATION:: Stanford University, Department of Computer Science, Numerical
               Analysis Project
       TITLE:: The truncated SVD as a method for regularization
        TYPE:: Manuscript
      AUTHOR:: Hansen, Per Christian
        DATE:: October 1986
       PAGES:: 18
    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 case of ill-conditioned matrices with a
               well-determined rank.
       NOTES:: [Adminitrivia V1/Prg/19960128]
         END:: STAN//NA-M-86-36