omputing the singular values of a bidiagonal matrix is the fin al phase of the standard algow rithm for the singular value decomposition of a general matrix. We present a new algorithm hich compu tes all the singular values of a bidiagonal matrix to high relative accuracy indepen- - p den t of their magn itudes. In contrast, the standard algorithm for bidiagonal matrices may com ute sm all singular values with no relative accuracy at all. Numerical experiments show that K the new algorithm is comparable in speed to the standard algorithm , and frequently faster. eywords: singular value decomposition , bidiagonal matrix, QR iteration 1 AMS(MOS) subject classifications: 65F20, 65G05, 65F35 . Introduction The standard algorithm for computing the singular value decomposition ( SVD ) of a gen1 eral real matrix A has two phases 7: ) Compute orthogonal matrices P and Q such that B = P AQ is in bidiagonal form , i.e. 1 1 1 T 1 . 2 has nonzero en tries only on its diagonal and first su...
Description
CiteSeerX — Accurate Singular Values of Bidiagonal Matrices
%0 Journal Article
%1 Demmel90accuratesingular
%A Demmel, James
%A Kahan, W.
%D 1990
%J SIAM J. Sci. Stat. Comput
%K algorithm svd
%P 873--912
%T Accurate Singular Values of Bidiagonal Matrices
%U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.3740
%V 11
%X omputing the singular values of a bidiagonal matrix is the fin al phase of the standard algow rithm for the singular value decomposition of a general matrix. We present a new algorithm hich compu tes all the singular values of a bidiagonal matrix to high relative accuracy indepen- - p den t of their magn itudes. In contrast, the standard algorithm for bidiagonal matrices may com ute sm all singular values with no relative accuracy at all. Numerical experiments show that K the new algorithm is comparable in speed to the standard algorithm , and frequently faster. eywords: singular value decomposition , bidiagonal matrix, QR iteration 1 AMS(MOS) subject classifications: 65F20, 65G05, 65F35 . Introduction The standard algorithm for computing the singular value decomposition ( SVD ) of a gen1 eral real matrix A has two phases 7: ) Compute orthogonal matrices P and Q such that B = P AQ is in bidiagonal form , i.e. 1 1 1 T 1 . 2 has nonzero en tries only on its diagonal and first su...
@article{Demmel90accuratesingular,
abstract = {omputing the singular values of a bidiagonal matrix is the fin al phase of the standard algow rithm for the singular value decomposition of a general matrix. We present a new algorithm hich compu tes all the singular values of a bidiagonal matrix to high relative accuracy indepen- - p den t of their magn itudes. In contrast, the standard algorithm for bidiagonal matrices may com ute sm all singular values with no relative accuracy at all. Numerical experiments show that K the new algorithm is comparable in speed to the standard algorithm , and frequently faster. eywords: singular value decomposition , bidiagonal matrix, QR iteration 1 AMS(MOS) subject classifications: 65F20, 65G05, 65F35 . Introduction The standard algorithm for computing the singular value decomposition ( SVD ) of a gen1 eral real matrix A has two phases [7]: ) Compute orthogonal matrices P and Q such that B = P AQ is in bidiagonal form , i.e. 1 1 1 T 1 . 2 has nonzero en tries only on its diagonal and first su...},
added-at = {2009-08-05T19:47:41.000+0200},
author = {Demmel, James and Kahan, W.},
biburl = {https://www.bibsonomy.org/bibtex/216c2df1b40001454483df74547ce13c4/folke},
description = {CiteSeerX — Accurate Singular Values of Bidiagonal Matrices},
interhash = {175297e82f7c9ddfb8feb5b67abcfdd9},
intrahash = {16c2df1b40001454483df74547ce13c4},
journal = {SIAM J. Sci. Stat. Comput},
keywords = {algorithm svd},
pages = {873--912},
timestamp = {2009-08-05T19:47:41.000+0200},
title = {Accurate Singular Values of Bidiagonal Matrices},
url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.48.3740},
volume = 11,
year = 1990
}