Preconditioned GMRES methods with incomplete Givens orthogonalization method for large sparse least-squares problems
type: Item
instance of: scholarly article
title: Preconditioned GMRES methods with incomplete Givens orthogonalization method for large sparse least-squares problems
zbMATH Open document ID: 1160.65313
author: Jun-Feng Yin
author: Ken Hayami
published in: Journal of Computational and Applied Mathematics
publication date: 2009-03-30T00:00:00Z
Mathematics Subject Classification ID: 65F20
Mathematics Subject Classification ID: 65F25
Mathematics Subject Classification ID: 65F50
Mathematics Subject Classification ID: 65F35
zbMATH DE Number: 5534922
zbMATH Keywords: least-squares problems
zbMATH Keywords: incomplete Givens orthogonalization methods
zbMATH Keywords: preconditioner
zbMATH Keywords: large sparse matrices
zbMATH Keywords: comparison of methods
zbMATH Keywords: generalized minimal residual (GMRES) method
zbMATH Keywords: numerical experiments
zbMATH Keywords: conjugate gradient least-squares method
describes a project that uses: SparseMatrix
describes a project that uses: LSQR
describes a project that uses: CRAIG
MaRDI profile type: Publication
full work available at URL: j.cam.2008.05.052
OpenAlex ID: W2072708752
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DOI: 10.1016/J.CAM.2008.05.052
description: scientific article; zbMATH DE number 5534922