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Note to the convergence of minimum residual HSS method.

Authors :
Ameri, Arezo
Beik, Fatemeh Panjeh Ali
Source :
Journal of Mathematical Modeling (JMM); Spring2021, Vol. 9 Issue 2, p323-330, 8p
Publication Year :
2021

Abstract

The minimum residual HSS (MRHSS) method is proposed in [BIT Numerical Mathematics, 59 (2019) 299{319] and its convergence analysis is proved under a certain condition. More recently in [Appl. Math. Lett. 94 (2019) 210{216], an alternative version of MRHSS is presented which converges unconditionally. In general, as the second approach works with a weighted inner product, it consumes more CPU time than MRHSS to converge. In the current work, we revisit the convergence analysis of the MRHSS method using a different strategy and state the convergence result for general two-step iterative schemes. It turns out that a special choice of parameters in the MRHSS results in an unconditionally convergent method without using a weighted inner product. Numerical experiments confirm the validity of established results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2345394X
Volume :
9
Issue :
2
Database :
Complementary Index
Journal :
Journal of Mathematical Modeling (JMM)
Publication Type :
Academic Journal
Accession number :
149343868
Full Text :
https://doi.org/10.22124/jmm.2020.18109.1559