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  4. Large-scale Tikhonov regularization via reduction by orthogonal projection
 
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Large-scale Tikhonov regularization via reduction by orthogonal projection

Publikationstyp
Journal Article
Date Issued
2011-09-23
Sprache
English
Author(s)
Lampe, Jörg  
Reichel, Lothar  
Voß, Heinrich 
Institut
Mathematik E-10  
TORE-URI
http://hdl.handle.net/11420/3378
Journal
Linear algebra and its applications  
Volume
436
Issue
8
Start Page
2845
End Page
2865
Citation
Linear Algebra and Its Applications 8 (436): 2845-2865 (2012)
Publisher DOI
10.1016/j.laa.2011.07.019
Scopus ID
2-s2.0-84858070336
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.
Subjects
Discrepancy principle
General-form Tikhonov regularization
Ill-posedness
Least squares
DDC Class
510: Mathematik
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