The preconditioned Gauss-Seidel method faster than the SOR method

DOI10.1016/j.cam.2007.07.002zbMath1158.65023OpenAlexW2098356380MaRDI QIDQ935766

Munenori Morimoto, Hiroshi Niki, Toshiyuki Kohno

Publication date: 8 August 2008

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2007.07.002

zbMATH Keywords

convergencenumerical examplespreconditioningsplittingGauss-Seidel methodM-matrixsuccessive overrelaxation (SOR)

Mathematics Subject Classification ID

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

Related Items (5)

An extended \(GS\) method for dense linear systems ⋮ A parallel bio-inspired shortest path algorithm ⋮ Convergence analysis of the new splitting preconditioned SOR‐type iterative methods for the linear system ⋮ Erratum to: ``A note on the preconditioned Gauss-Seidel method for \(M\)-matrices ⋮ Two new modified Gauss-Seidel methods for linear system with M-matrices

Cites Work

• Unnamed Item
• Modified iterative methods for consistent linear systems
• Comparisons of nonnegative splittings of matrices
• On optimal improvements of classical iterative schemes for \(Z\)-matrices
• Improving the modified Gauss-Seidel method for \(Z\)-matrices
• The survey of preconditioners used for accelerating the rate of convergence in the Gauss-Seidel method.
• A comparison theorem for the iterative method with the preconditioner \((I+S_{max})\)
• The Gauss-Seidel iterative method with the preconditioning matrix \((I+S+S_m)\)
• Accelerated iterative method for \(Z\)-matrices
• Adaptive gauss-seidel method for linear systems
• Matrix theory. Basic results and techniques

This page was built for publication: The preconditioned Gauss-Seidel method faster than the SOR method