A parallel preconditioned modified conjugate gradient method for large Sylvester matrix equation
type: Item
instance of: scholarly article
title: A parallel preconditioned modified conjugate gradient method for large Sylvester matrix equation
zbMATH Open document ID: 1407.65047
DOI: 10.1155/2014/598716
author: Junxia Hou
author: Quanyi Lv
author: Manyu Xiao
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: Computational effort of solving large-scale Sylvester equations \(\mathbf{A} \mathbf{X} + \mathbf{X} \mathbf{B} + \mathbf{F} = \mathbf{O}\) is frequently hindered in dealing with many complex control problems. In this work, a parallel preconditioned algorithm for solving it is proposed based on combination of a parameter iterative preconditioned method and modified form of conjugate gradient (MCG) method. Furthermore, Schur's inequality and modified conjugate gradient method are employed to overcome the involved difficulties such as determination of parameter and calculation of inverse matrix. Several numerical results finally show that high performance of proposed parallel algorithm is obtained both in convergent rate and in parallel efficiency.
Mathematics Subject Classification ID: 65F30
Mathematics Subject Classification ID: 15A24
zbMATH DE Number: 7016822
describes a project that uses: Algorithm 432
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/598716
OpenAlex ID: W2000686592
Wikidata QID: Q59066401
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description: scientific article; zbMATH DE number 7016822