A Jacobi--Davidson Type SVD Method
From MaRDI portal
Publication:2780543
DOI10.1137/S1064827500372973zbMath1002.65048MaRDI QIDQ2780543
Publication date: 15 April 2002
Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)
normsingular valuessingular vectorscorrection equationJacobi-Davidson methodsingular value decomposition (SVD)augmented matrix(inexact) accelerated Newton methodimproving singular values
Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Numerical solutions to overdetermined systems, pseudoinverses (65F20) Numerical computation of matrix norms, conditioning, scaling (65F35)
Related Items (30)
A Preconditioned Hybrid SVD Method for Accurately Computing Singular Triplets of Large Matrices ⋮ Majorization bounds for SVD ⋮ Probabilistic Bounds for the Matrix Condition Number with Extended Lanczos Bidiagonalization ⋮ On Approximate Reduction of Multi-Port Resistor Networks ⋮ An implicitly restarted block Lanczos bidiagonalization method using Leja shifts ⋮ Grassmann algorithms for low rank approximation of matrices with missing values ⋮ An efficient, memory-saving approach for the Loewner framework ⋮ Restarted block Lanczos bidiagonalization methods ⋮ Projected Tikhonov regularization of large-scale discrete ill-posed problems ⋮ Verified inclusions for a nearest matrix of specified rank deficiency via a generalization of Wedin's \(\sin (\theta)\) theorem ⋮ Computing several eigenvalues of nonlinear eigenvalue problems by selection ⋮ Low-Rank Solution of Unsteady Diffusion Equations with Stochastic Coefficients ⋮ GCV for Tikhonov regularization by partial SVD ⋮ Accuracy of singular vectors obtained by projection-based SVD methods ⋮ A smallest singular value method for nonlinear eigenvalue problems ⋮ A Krylov-Schur approach to the truncated SVD ⋮ Low-rank incremental methods for computing dominant singular subspaces ⋮ Iterative computation of the smallest singular value and the corresponding singular vectors of a matrix. ⋮ Probabilistic upper bounds for the matrix two-norm ⋮ On the convergence of Krylov methods with low-rank truncations ⋮ A Jacobi-Davidson type method for the product eigenvalue problem ⋮ The Jacobi-Davidson method ⋮ A DEIM Induced CUR Factorization ⋮ A model reduction approach for inverse problems with operator valued data ⋮ PRIMME_SVDS: A High-Performance Preconditioned SVD Solver for Accurate Large-Scale Computations ⋮ A Jacobi-Davidson type method for the generalized singular value problem ⋮ On Inner Iterations of Jacobi--Davidson Type Methods for Large SVD Computations ⋮ A Golub--Kahan Davidson Method for Accurately Computing a Few Singular Triplets of Large Sparse Matrices ⋮ Computing smallest singular triplets with implicitly restarted Lanczos bidiagonalization ⋮ Harmonic and refined extraction methods for the singular value problem, with applications in least squares problems
This page was built for publication: A Jacobi--Davidson Type SVD Method