In this paper we consider the problem of approximating the solution of infinite linear systems, finitely expressed by a sparse coefficient matrix. We analyse an algorithm based on Krylov subspace methods embedded in an adaptive enlargement scheme. The management of the algorithm is not trivial, due to the irregular convergence behaviour frequently displayed by Krylov subspace methods for nonsymmetric systems. Numerical experiments, carried out on several test problems, indicate that the more robust methods, such as GMRES and QMR, embedded in the adaptive enlargement scheme, exhibit good performances. (C) 2006 Elsevier B.V. All rights reserved.
Adaptive solution of infinite linear systems by Krylov subspace methods / P., Favati; Lotti, Grazia; O., Menchi; F., Romani. - In: JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS. - ISSN 0377-0427. - 210:(2007), pp. 191-199. [10.1016/j.cam.2006.10.063]
Adaptive solution of infinite linear systems by Krylov subspace methods
LOTTI, Grazia;
2007-01-01
Abstract
In this paper we consider the problem of approximating the solution of infinite linear systems, finitely expressed by a sparse coefficient matrix. We analyse an algorithm based on Krylov subspace methods embedded in an adaptive enlargement scheme. The management of the algorithm is not trivial, due to the irregular convergence behaviour frequently displayed by Krylov subspace methods for nonsymmetric systems. Numerical experiments, carried out on several test problems, indicate that the more robust methods, such as GMRES and QMR, embedded in the adaptive enlargement scheme, exhibit good performances. (C) 2006 Elsevier B.V. All rights reserved.File | Dimensione | Formato | |
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