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Large-scale Tikhonov regularization via reduction by orthogonal projection
Publikationstyp
Journal Article
Publikationsdatum
2011-09-23
Sprache
English
Author
Institut
TORE-URI
Enthalten in
Volume
436
Issue
8
Start Page
2845
End Page
2865
Citation
Linear Algebra and Its Applications 8 (436): 2845-2865 (2012)
Publisher DOI
Scopus ID
Publisher
American Elsevier Publ.
This paper presents a new approach to computing an approximate solution of Tikhonov-regularized large-scale ill-posed least-squares problems with a general regularization matrix. The iterative method applies a sequence of projections onto generalized Krylov subspaces. A suitable value of the regularization parameter is determined by the discrepancy principle.
Schlagworte
Discrepancy principle
General-form Tikhonov regularization
Ill-posedness
Least squares
DDC Class
510: Mathematik