Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4639088 | Journal of Computational and Applied Mathematics | 2014 | 16 Pages |
Abstract
In the framework of iterative regularization techniques for large-scale linear ill-posed problems, this paper introduces a novel algorithm for the choice of the regularization parameter when performing the Arnoldi–Tikhonov method. Assuming that we can apply the discrepancy principle, this new strategy can work without restrictions on the choice of the regularization matrix. Moreover, this method is also employed as a procedure to detect the noise level whenever it is just overestimated. Numerical experiments arising from the discretization of integral equations and image restoration are presented.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Silvia Gazzola, Paolo Novati,