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Note to the convergence of minimum residual HSS method.
- 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