A Divide-and-Conquer Algorithm for the Bidiagonal SVD
From MaRDI portal
Publication:4325679
DOI10.1137/S0895479892242232zbMath0821.65019MaRDI QIDQ4325679
Publication date: 13 March 1995
Published in: SIAM Journal on Matrix Analysis and Applications (Search for Journal in Brave)
singular value decompositionsingular vectorsbidiagonal matrixbidiagonal divide-and-conquer algorithm
Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Numerical solutions to overdetermined systems, pseudoinverses (65F20)
Related Items (24)
Computing Fundamental Matrix Decompositions Accurately via the Matrix Sign Function in Two Iterations: The Power of Zolotarev's Functions ⋮ The Singular Value Decomposition: Anatomy of Optimizing an Algorithm for Extreme Scale ⋮ An Accelerated Divide-and-Conquer Algorithm for the Bidiagonal SVD Problem ⋮ A Fast Contour-Integral Eigensolver for Non-Hermitian Matrices ⋮ Forward stable eigenvalue decomposition of rank-one modifications of diagonal matrices ⋮ Low-rank tensor methods for partial differential equations ⋮ Dynamic normal forms and dynamic characteristic polynomial ⋮ Look-ahead in the two-sided reduction to compact band forms for symmetric eigenvalue problems and the SVD ⋮ Accurate eigenvalue decomposition of real symmetric arrowhead matrices and applications ⋮ Analytical Low-Rank Compression via Proxy Point Selection ⋮ On homogeneous least-squares problems and the inconsistency introduced by mis-constraining ⋮ Accurate polynomial root-finding methods for symmetric tridiagonal matrix eigenproblems ⋮ Computation of Gauss-type quadrature formulas ⋮ An improved divide-and-conquer algorithm for the banded matrices with narrow bandwidths ⋮ Linear algebra software for large-scale accelerated multicore computing ⋮ Restructuring the Tridiagonal and Bidiagonal QR Algorithms for Performance ⋮ A new stable bidiagonal reduction algorithm ⋮ A Lanczos bidiagonalization algorithm for Hankel matrices ⋮ Superfast Divide-and-Conquer Method and Perturbation Analysis for Structured Eigenvalue Solutions ⋮ Numerical methods for accurate computation of the eigenvalues of Hermitian matrices and the singular values of general matrices ⋮ An \({\mathcal O}(n^{2})\) algorithm for the bidiagonal SVD ⋮ Highly accurate symmetric eigenvalue decomposition and hyperbolic SVD ⋮ Deflation for the Symmetric Arrowhead and Diagonal-Plus-Rank-One Eigenvalue Problems ⋮ A High Performance QDWH-SVD Solver Using Hardware Accelerators
This page was built for publication: A Divide-and-Conquer Algorithm for the Bidiagonal SVD
