Solving large and sparse linear least-squares problems by conjugate gradient algorithms
type: Item
instance of: scholarly article
title: Solving large and sparse linear least-squares problems by conjugate gradient algorithms
zbMATH Open document ID: 0644.65028
DOI: 10.1016/0898-1221(88)90170-8
author: B. George
publication date: 1988-01-01T00:00:00Z
review text: Large and sparse least squares problems are transformed into equivalent problems which have a symmetric and positivedefinite matrix by a certain decomposition technique. The conjugate gradient algorithm (CG) is applied in the solution of the later problem. Numerical examples are performed with well-known test problems. The results illustrate that the CG algorithms applied to the modified problems is very efficient for some classes of problems.
Mathematics Subject Classification ID: 65F20
Mathematics Subject Classification ID: 65F10
Mathematics Subject Classification ID: 65F50
zbMATH DE Number: 4050860
zbMATH Keywords: Large and sparse least squares problems
zbMATH Keywords: decomposition technique
zbMATH Keywords: conjugate gradient algorithm
zbMATH Keywords: Numerical examples
reviewed by: József Abaffy
describes a project that uses: LINPACK
MaRDI profile type: Publication
full work available at URL: 0898-1221(88)90170-8
OpenAlex ID: W2067576119
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published in: Computers & Mathematics with Applications
description: scientific article; zbMATH DE number 4050860