Hochstenbach, Michiel E. A Jacobi–Davidson type SVD method. (English) Zbl 1002.65048 SIAM J. Sci. Comput. 23, No. 2, 606-628 (2001). Author’s summary: We discuss a new method for the iterative computation of a portion of the singular values and vectors of a large sparse matrix. Similar to the Jacobi-Davidson method for the equation. We give a few variants of this Jacobi-Davison singular value decomposition (JDSVD) method with their theoretical properties. It is shown that the JDSVD can be seen as an accelerated (inexact) Newton scheme. We experimentally compare the method with some other iterative SVD methods. Reviewer: B.Döring (Düsseldorf) Cited in 30 Documents MSC: 65F20 Numerical solutions to overdetermined systems, pseudoinverses 65F15 Numerical computation of eigenvalues and eigenvectors of matrices 65F35 Numerical computation of matrix norms, conditioning, scaling Keywords:singular value decomposition (SVD); singular values; singular vectors; norm; augmented matrix; correction equation; (inexact) accelerated Newton method; improving singular values; Jacobi-Davidson method PDFBibTeX XMLCite \textit{M. E. Hochstenbach}, SIAM J. Sci. Comput. 23, No. 2, 606--628 (2001; Zbl 1002.65048) Full Text: DOI