A Global Property of Restarted FOM Algorithm
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@Article{JICS-1-11,
author = {},
title = {A Global Property of Restarted FOM Algorithm},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {1},
number = {1},
pages = {11--20},
abstract = { In this paper an interesting property of the restarted FOM algorithm for solving large
nonsymmetric linear systems is presented and studied. By establishing a relationship between the
convergence of its residual vectors and the convergence of Ritz values in the Arnoldi procedure, it is shown
that some important information of previous FOM(m) cycles may be saved by the iteration approximates at
the time of restarting, with which the FOM(m) cycles can complement one another harmoniously in reducing
the iteration residual. Based on the study of FOM(m), two polynomial preconditioning techniques are
proposed; one is for solving nonsymmetric linear systems and another is for forming an effective starting
vector in the restarted Arnoldi method for solving nonsymmetric eigenvalue problems.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22855.html}
}
TY - JOUR
T1 - A Global Property of Restarted FOM Algorithm
AU -
JO - Journal of Information and Computing Science
VL - 1
SP - 11
EP - 20
PY - 2024
DA - 2024/01
SN - 1
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22855.html
KW - nonsymmetric linear systems, nonsymmetric eigenvalue problems, iterative methods, FOM,
Arnoldi’s method, restarting
KW - polynomial preconditioning.
AB - In this paper an interesting property of the restarted FOM algorithm for solving large
nonsymmetric linear systems is presented and studied. By establishing a relationship between the
convergence of its residual vectors and the convergence of Ritz values in the Arnoldi procedure, it is shown
that some important information of previous FOM(m) cycles may be saved by the iteration approximates at
the time of restarting, with which the FOM(m) cycles can complement one another harmoniously in reducing
the iteration residual. Based on the study of FOM(m), two polynomial preconditioning techniques are
proposed; one is for solving nonsymmetric linear systems and another is for forming an effective starting
vector in the restarted Arnoldi method for solving nonsymmetric eigenvalue problems.
. (2024). A Global Property of Restarted FOM Algorithm.
Journal of Information and Computing Science. 1 (1).
11-20.
doi:
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