Relaxation techniques in the iterative '2\(\times 2'\) algorithm

DOI10.1016/S0045-7825(85)80004-9zbMath0554.65028OpenAlexW2089883297MaRDI QIDQ760163

R. M. Quick, M. C. Steenkamp, H. G. Miller

Publication date: 1985

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0045-7825(85)80004-9

zbMATH Keywords

numerical examplerelaxationconvergence rateHermitian matrixdominant eigenstate

Mathematics Subject Classification ID

Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Iterative numerical methods for linear systems (65F10)

Related Items (1)

A two-step iterative block Lanczos algorithm for a dominant eigenspan

Uses Software

• NAG
• nag
• C05ADF

Cites Work

• Preconditioned iterative methods for the large sparse symmetric eigenvalue problem
• Iterative eigenvalue algorithms based on convergent splittings
• A method for calculating the extreme eigensolution of a real symmetric matrix of high order
• An iterative method for calculating low lying eigenvalues of an Hermitian operator

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