On Accuracy Properties of One-Sided Bidiagonalization Algorithm and Its Applications

Nela Bosner () and Zlatko Drmač ()
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Nela Bosner: University of Zagreb, Department of Mathematics
Zlatko Drmač: University of Zagreb, Department of Mathematics

A chapter in Proceedings of the Conference on Applied Mathematics and Scientific Computing, 2005, pp 141-150 from Springer

Abstract: Abstract The singular value decomposition (SVD) of a general matrix is the fundamental theoretical and computational tool in numerical linear algebra. The most efficient way to compute the SVD is to reduce the matrix to bidiagonal form in a finite number of orthogonal (unitary) transformations, and then to compute the bidiagonal SVD. This paper gives detailed error analysis and proposes modifications of recently proposed one-sided bidiagonalization procedure, suitable for parallel computing. It also demonstrates its application in solving two common problems in linear algebra.

Keywords: Singular Value Decomposition; Versus Versus Versus; Numerical Linear Algebra; Bidiagonal Form; Bidiagonalization Algorithm (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4020-3197-7_8

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DOI: 10.1007/1-4020-3197-1_8

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