FOM-inverse vector iteration method for computing a few smallest (largest) eigenvalues of pair (A,B)

DOI10.1016/j.amc.2006.10.019zbMath1120.65047OpenAlexW4241324887MaRDI QIDQ2371475

A. Refahi, H. Saberi Najafi

Publication date: 4 July 2007

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

Full work available at URL: https://doi.org/10.1016/j.amc.2006.10.019

zbMATH Keywords

numerical examplesdeflationlargest eigenvaluesmallest eigenvaluesymmetric matrixArnoldi processKrylov subspacefull orthogonalization methodinner-outer iterationFOM

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15)

Related Items

A new algorithm for solving large-scale generalized eigenvalue problem based on projection methods ⋮ Stability analysis of distributed-order Hilfer-Prabhakar systems based on inertia theory ⋮ New iterative methods for generalized singular-value problems ⋮ Weighted FOM-inverse vector iteration method for computing a few smallest (largest) eigenvalues of pair (A, B)

Uses Software

• eigs

Cites Work

• Unnamed Item
• Weighted FOM and GMRES for solving nonsymmetric linear systems
• A new restarting method in the Arnoldi algorithm for computing the eigenvalues of a nonsymmetric matrix
• Weighted restarting method in the weighted Arnoldi algorithm for computing the eigenvalues of a nonsymmetric matrix
• Krylov Subspace Methods for Solving Large Unsymmetric Linear Systems
• Implicit Application of Polynomial Filters in a k-Step Arnoldi Method
• Dynamic Thick Restarting of the Davidson, and the Implicitly Restarted Arnoldi Methods
• On restarting the Arnoldi method for large nonsymmetric eigenvalue problems
• ILUM: A Multi-Elimination ILU Preconditioner for General Sparse Matrices

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