Preconditioned RRGMRES for Discrete Ill-Posed Problems-Reference-Cited by-同舟云学术

Preconditioned RRGMRES for Discrete Ill-Posed Problems

Published:2018-05-24 Issue:04 Volume:15 Page:1850023
ISSN:0219-8762
Container-title:International Journal of Computational Methods
language:en
Short-container-title:Int. J. Comput. Methods

Author:

Aminikhah H.¹,Yousefi M.¹

Affiliation:

1. Department of Applied Mathematics and Computer Sciences, Faculty of Mathematical Sciences, University of Guilan, P. O. Box 41938-19141, Rasht, Iran

Abstract

Range Restricted GMRES (RRGMRES) can be considered as regularizing iterative method and its iterates as regularized solutions. In this paper, we use two preconditioned versions of this method for solving ill-posed inverse problems. Our proposed preconditioner matrix is appropriate to use directly for linear systems of the form [Formula: see text] with square ill-conditioned coefficient matrix. We show numerically that the Preconditioned RRGMRES method has more stable solution compared to RRGMRES.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computational Mathematics,Computer Science (miscellaneous)

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0219876218500238

Reference22 articles.

1. Numerical Methods in Matrix Computations

2. An improved preconditioned LSQR for discrete ill-posed problems

3. Preconditioned iterative methods for linear discrete ill-posed problems from a Bayesian inversion perspective

4. GMRES-type methods for inconsistent systems

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