Conjugate gradient and minimal residual method for solving symmetric indefinite systems
type: Item
instance of: scholarly article
title: Conjugate gradient and minimal residual method for solving symmetric indefinite systems
zbMATH Open document ID: 0888.65025
DOI: 10.1016/S0377-0427(97)00127-1
author: Yu-Ling Lai
author: Wen-Wei Lin
author: Dan'l Pierce
published in: Journal of Computational and Applied Mathematics
publication date: 1998-06-11T00:00:00Z
review text: A norm-minimizing-type algorithm based on the conjugate gradient approach for solving large sparse linear systems with symmetric and indefinite coefficient matrices is proposed. Some relations among the search directions and the residuals, and how the search directions are related to the Krylov subspace, are investigated. Some numerical examples are illustrated to show its convergence properties.
Mathematics Subject Classification ID: 65F10
Mathematics Subject Classification ID: 65F50
zbMATH DE Number: 1084115
zbMATH Keywords: minimal residual method
zbMATH Keywords: symmetric indefinite systems
zbMATH Keywords: conjugate gradient
zbMATH Keywords: large sparse linear systems
zbMATH Keywords: Krylov subspace
zbMATH Keywords: numerical examples
reviewed by: Shenquan Xie
describes a project that uses: Harwell-Boeing sparse matrix collection
MaRDI profile type: Publication
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Wikidata QID: Q126382616
full work available at URL: s0377-0427(97)00127-1
OpenAlex ID: W1976157534
description: scientific article; zbMATH DE number 1084115