On preconditionad iterative methods for solving (A-lambdaB)x=0

DOI10.1007/BF02253688zbMath0518.65019OpenAlexW358344376MaRDI QIDQ1054118

David J. Evans

Publication date: 1984

Published in: Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02253688

zbMATH Keywords

conjugate gradient algorithmextreme eigenvalueslarge sparse matricespreconditioned iterative methodgeneralised eigenvalue problem

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Numerical methods for eigenvalue problems for boundary value problems involving PDEs (65N25) Numerical solution of eigenvalue problems involving ordinary differential equations (65L15)

Related Items (1)

On iterative methods for solving a semi-linear eigenvalue problem

Cites Work

• Unnamed Item
• On the preconditioned Jacobi method for solving large linear systems
• Iterative eigenvalue algorithms based on convergent splittings
• Basic numerical mathematics. Vol. 2: Numerical algebra
• 𝑆𝑂𝑅-methods for the eigenvalue problem with large sparse matrices
• Hyperbolic Pairs in the Method of Conjugate Gradients
• The Use of Pre-conditioning in Iterative Methods for Solving Linear Equations with Symmetric Positive Definite Matrices
• The method of conjugate gradients used in inverse iteration
• Methods of conjugate gradients for solving linear systems

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