Title
Generalized singular value decomposition with iterated Tikhonov regularization
Abstract
Linear discrete ill-posed problems arise in many areas of science and engineering. Their solutions are very sensitive to perturbations in the data. Regularization methods try to reduce the sensitivity by replacing the given problem by a nearby one, whose solution is less affected by perturbations. This paper describes how generalized singular value decomposition can be combined with iterated Tikhonov regularization and illustrates that the method so obtained determines approximate solutions of higher quality than the more commonly used approach of pairing generalized singular value decomposition with (standard) Tikhonov regularization. The regularization parameter is determined with the aid of the discrepancy principle. This requires the application of a zero-finder. Several zero-finders are compared.
Year
DOI
Venue
2020
10.1016/j.cam.2019.05.024
Journal of Computational and Applied Mathematics
Keywords
Field
DocType
Ill-posed problem,Iterated Tikhonov,GSVD,Zero-finder
Tikhonov regularization,Generalized singular value decomposition,Mathematical analysis,Pairing,Regularization (mathematics),Iterated function,Mathematics,Perturbation (astronomy)
Journal
Volume
Issue
ISSN
373
C
0377-0427
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Alessandro Buccini111.70
Mirjeta Pasha200.34
Lothar Reichel345395.02