===firstname:
Ian
===firstname3:

===affil6:

===lastname3:

===email:
i.n.zwaan@tue.nl
===keyword_other2:

===lastname6:

===affil5:

===lastname4:

===lastname7:

===affil7:

===postal:
Department of Mathematics and Computer Science
Eindhoven University of Technology
PO Box 513
NL-5600 MB Eindhoven
The Netherlands
===ABSTRACT:
Tikhonov regularization is a popular method to approximate solutions of linear discrete ill-posed problems when the observed or measured data is contaminated by noise.  Multi-parameter Tikhonov regularization may improve the quality of the computed approximate solutions. We propose a new iterative method for large-scale multi-parameter Tikhonov regularization with general regularization operators based on a multidirectional subspace expansion. This expansion may be combined with subspace truncation to avoid excessive growth of the search space. Furthermore, we introduce a simple and effective parameter selection strategy based on the discrepancy principle and related to perturbation results.

===affil3:

===title:
Multidirectional subspace expansion for single-parameter and multi-parameter Tikhonov regularization
===affil2:
Eindhoven University of Technology
===lastname2:
Hochstenbach
===firstname4:

===keyword1:
Inverse problems, regularization
===workshop:
no
===lastname:
Zwaan
===firstname5:

===keyword2:
Iterative methods in imaging
===otherauths:

===affil4:

===competition:
yes
===firstname7:

===firstname6:

===keyword_other1:

===lastname5:

===affilother:

===firstname2:
Michiel E.