Using semiseparable matrices to compute the SVD of a general matrix product/quotient

DOI10.1016/J.CAM.2010.02.007zbMath1196.65078OpenAlexW2167278008MaRDI QIDQ989125

Yvette Vanberghen, Marc Van Barel, Paul Van Dooren

Publication date: 27 August 2010

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cam.2010.02.007

zbMATH Keywords

numerical examplesreduction algorithmsingular value decomposition (SVD)nested subspace iterationupper triangular semiseparable matrix

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20)

Cites Work

• A QR-method for computing the singular values via semiseparable matrices
• An accurate product SVD algorithm
• Computing the SVD of a General Matrix Product/Quotient
• Computing the Singular Value Decomposition of a Product of Two Matrices
• Generalizations of the Singular Value and QR-Decompositions
• Calculating the Singular Values and Pseudo-Inverse of a Matrix

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