|Publisher DOI:||10.1016/j.laa.2011.07.019||Title:||Large-scale Tikhonov regularization via reduction by orthogonal projection||Language:||English||Authors:||Lampe, Jörg
|Keywords:||Discrepancy principle; General-form Tikhonov regularization; Ill-posedness; Least squares||Issue Date:||23-Sep-2011||Publisher:||American Elsevier Publ.||Source:||Linear Algebra and Its Applications 8 (436): 2845-2865 (2012)||Abstract (english):||
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.
|URI:||http://hdl.handle.net/11420/3378||ISSN:||0024-3795||Journal:||Linear algebra and its applications||Institute:||Mathematik E-10||Document Type:||Article|
|Appears in Collections:||Publications without fulltext|
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