Reduction of a General Matrix to Tridiagonal Form
- 1 April 1991
- journal article
- Published by Society for Industrial & Applied Mathematics (SIAM) in SIAM Journal on Matrix Analysis and Applications
- Vol. 12 (2), 362-373
- https://doi.org/10.1137/0612026
Abstract
An algorithm for reducing a nonsymmetric matrix to tridiagonal form as a first step toward finding its eigenvalues is described. The algorithm uses a variation of threshold pivoting, where at each step, the pivot is chosen to minimize the maximum entry in the transformation matrix that reduces the next column and row of the matrix. Situations are given where the tridiagonalization process breaks down, and two recovery methods are presented for these situations. Although no existing tridiagonalization algorithm is guaranteed to succeed, this algorithm is found to be very robust and fast in practice. A gradual loss of similarity is also observed as the order of the matrix increases.Keywords
This publication has 8 references indexed in Scilit:
- Reduction to Tridiagonal Form and Minimal RealizationsSIAM Journal on Matrix Analysis and Applications, 1992
- Self-equivalent flows associated with the generalized eigenvalue problemLinear Algebra and its Applications, 1989
- Improving the Accuracy of Computed Eigenvalues and EigenvectorsSIAM Journal on Numerical Analysis, 1983
- The ELR Method for Computing the Eigenvalues of a General MatrixSIAM Journal on Numerical Analysis, 1981
- Matrix Eigensystem Routines — EISPACK GuidePublished by Springer Nature ,1974
- The reduction of an arbitrary real square matrix to tridiagonal form using similarity transformationsMathematics of Computation, 1963
- The QR Transformation--Part 2The Computer Journal, 1962
- The Reduction of a Matrix to Codiagonal Form by EliminationsThe Computer Journal, 1961