A Lanczos bidiagonalization algorithm for Hankel matrices

DOI10.1016/j.laa.2008.01.012zbMath1158.65027OpenAlexW1983942331MaRDI QIDQ1002256

Kevin Browne, Yi-Min Wei, Sanzheng Qiao

Publication date: 25 February 2009

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.laa.2008.01.012

zbMATH Keywords

numerical experimentsHankel matrixLanczos bidiagonalizationmatrix-vector multiplicationsingular value decomposition (SVD)algorithm stabilityfast Hankel SVD

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20) Orthogonalization in numerical linear algebra (65F25)

Related Items (8)

High-order sum-of-squares structured tensors: theory and applications ⋮ An efficient quantum algorithm for spectral estimation ⋮ Fast ESPRIT algorithms based on partial singular value decompositions ⋮ A fast SVD for multilevel block Hankel matrices with minimal memory storage ⋮ Inheritance properties and sum-of-squares decomposition of Hankel tensors: theory and algorithms ⋮ Fast Hankel tensor–vector product and its application to exponential data fitting ⋮ Bilinear Lanczos components for fast dimensionality reduction and feature extraction ⋮ \textsc{mxpfit}: a library for finding optimal multi-exponential approximations

Cites Work

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• Multiple representations to compute orthogonal eigenvectors of symmetric tridiagonal matrices
• A fast eigenvalue algorithm for Hankel matrices
• A fast symmetric SVD algorithm for square Hankel matrices
• The Lanczos Algorithm With Partial Reorthogonalization
• A Divide-and-Conquer Algorithm for the Bidiagonal SVD

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