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It is shown that the basic regularization procedures for finding
meaningful approximate solutions of ill-conditioned or singular linear
systems can be phrased and analyzed in terms of classical linear
algebra.
Apart from rewriting many known results in a more elegant form a new
two-parameter family of merit functions for the determination of the
regularization parameter is derived.
The traditional merit functions from generalized cross validation
(GCV) and generalized maximum likelihood (GML) are recovered as
special cases.
Frank Kiefer
2001-12-05
