Constraint preconditioners for solving singular saddle point problems
type: Item
instance of: scholarly article
title: Constraint preconditioners for solving singular saddle point problems
zbMATH Open document ID: 1257.65017
author: Nai-Min Zhang
author: Pan Shen
published in: Journal of Computational and Applied Mathematics
publication date: 2012-11-09T00:00:00Z
review text: The authors study constraint preconditioners for solving singular saddle point problems. They show that constraint preconditioners are constructed by proper splittings, and the corresponding generalized minimal residual method can determine the least squares solutions at breakdown. They also analyze properties of the preconditioned matrices, in particular their eigenvalue distributions.
Mathematics Subject Classification ID: 65F08
Mathematics Subject Classification ID: 15A18
Mathematics Subject Classification ID: 65F10
zbMATH DE Number: 6104516
zbMATH Keywords: singular saddle point system
zbMATH Keywords: constraint preconditioner
zbMATH Keywords: least squares solution
zbMATH Keywords: GMRES
zbMATH Keywords: convergence
zbMATH Keywords: eigenvalue distributions
zbMATH Keywords: generalized minimal residual method
reviewed by: Liu Xinguo
MaRDI profile type: Publication
full work available at URL: j.cam.2012.08.025
OpenAlex ID: W2066263304
DOI: 10.1016/J.CAM.2012.08.025
description: scientific article; zbMATH DE number 6104516