Preconditioners for the conjugate gradient algorithm using Gram–Schmidt and least squares methods

DOI10.1080/00207160601173621zbMath1126.65038OpenAlexW2105200839MaRDI QIDQ3438806

Julien Straubhaar

Publication date: 29 May 2007

Published in: International Journal of Computer Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207160601173621

zbMATH Keywords

preconditioningcondition numberconjugate gradient methodGram-Schmidt orthogonalizationleast squares

Mathematics Subject Classification ID

Iterative numerical methods for linear systems (65F10) Numerical computation of matrix norms, conditioning, scaling (65F35)

Cites Work

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• Preconditioning techniques for large linear systems: A survey
• Factorized Sparse Approximate Inverse Preconditionings I. Theory
• Iterative Solution Methods
• Parallel Preconditioning with Sparse Approximate Inverses
• A Sparse Approximate Inverse Preconditioner for the Conjugate Gradient Method

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