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Preconditioned iterative methods for linear discrete ill-posed problems from a Bayesian inversion perspective
- Source :
-
Journal of Computational & Applied Mathematics . Jan2007, Vol. 198 Issue 2, p378-395. 18p. - Publication Year :
- 2007
-
Abstract
- Abstract: In this paper we revisit the solution of ill-posed problems by preconditioned iterative methods from a Bayesian statistical inversion perspective. After a brief review of the most popular Krylov subspace iterative methods for the solution of linear discrete ill-posed problems and some basic statistics results, we analyze the statistical meaning of left and right preconditioners, as well as projected-restarted strategies. Computed examples illustrating the interplay between statistics and preconditioning are also presented. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 03770427
- Volume :
- 198
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Journal of Computational & Applied Mathematics
- Publication Type :
- Academic Journal
- Accession number :
- 22473559
- Full Text :
- https://doi.org/10.1016/j.cam.2005.10.038