Pages that link to "Item:Q3918995"
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The following pages link to A Block Lanczos Method for Computing the Singular Values and Corresponding Singular Vectors of a Matrix (Q3918995):
Displaying 39 items.
- On equivalence of fractional factorial designs based on singular value decomposition (Q394100) (← links)
- A GCV based Arnoldi-Tikhonov regularization method (Q398632) (← links)
- A harmonic Lanczos bidiagonalization method for computing interior singular triplets of large matrices (Q433291) (← links)
- A thick-restarted block Arnoldi algorithm with modified Ritz vectors for large eigenproblems (Q611385) (← links)
- Matrix-free Krylov iteration for implicit convolution of numerically low-rank data (Q738959) (← links)
- The stability robustness determination of state space models with real unstructured perturbations (Q809041) (← links)
- Restarted block Lanczos bidiagonalization methods (Q870765) (← links)
- A characterization of optimal scaling for structured singular value computation (Q919745) (← links)
- Block Krylov-Schur method for large symmetric eigenvalue problems (Q925250) (← links)
- Deflated block Krylov subspace methods for large scale eigenvalue problems (Q966072) (← links)
- Lanczos based preconditioner for discrete ill-posed problems (Q975318) (← links)
- A bidiagonalization algorithm for solving large and sparse ill-posed systems of linear equations (Q1111337) (← links)
- Iterative algorithms for computing the singular subspace of a matrix associated with its smallest singular values (Q1176528) (← links)
- Adaptive Lanczos methods for recursive condition estimation (Q1186619) (← links)
- Estimating the largest singular values of large sparse matrices via modified moments (Q1186625) (← links)
- An implicit shift bidiagonalization algorithm for ill-posed systems (Q1347073) (← links)
- Computation of the fundamental singular subspace of a large matrix (Q1355206) (← links)
- The ubiquitous Kronecker product (Q1591176) (← links)
- The block Lanczos algorithm for linear ill-posed problems (Q1675423) (← links)
- GCV for Tikhonov regularization by partial SVD (Q1689313) (← links)
- Approximate tensor-product preconditioners for very high order discontinuous Galerkin methods (Q1700740) (← links)
- Solution methods for linear discrete ill-posed problems for color image restoration (Q1783374) (← links)
- Nonequivalence deflation for the solution of matrix latent value problems (Q1906758) (← links)
- A modified harmonic block Arnoldi algorithm with adaptive shifts for large interior eigen\-problems (Q2372934) (← links)
- An implicitly restarted block Lanczos bidiagonalization method using Leja shifts (Q2376857) (← links)
- An implicitly restarted Lanczos bidiagonalization method with refined harmonic shifts for computing smallest singular triplets (Q2511197) (← links)
- Approximating dominant singular triplets of large sparse matrices via modified moments (Q2564505) (← links)
- Large-Scale Inverse Problems in Imaging (Q2789799) (← links)
- Mathematical modeling of semiconductor quantum dots based on the nonparabolic effective-mass approximation (Q2852189) (← links)
- Matrices with Hierarchical Low-Rank Structures (Q2971626) (← links)
- A Preconditioned Hybrid SVD Method for Accurately Computing Singular Triplets of Large Matrices (Q3447456) (← links)
- A Hybrid LSMR Algorithm for Large-Scale Tikhonov Regularization (Q3449797) (← links)
- Matrix-free iterative solution strategies for large dense linear systems (Q4383430) (← links)
- Fast Solvers for Two-Dimensional Fractional Diffusion Equations Using Rank Structured Matrices (Q5230663) (← links)
- Generalized Hybrid Iterative Methods for Large-Scale Bayesian Inverse Problems (Q5372617) (← links)
- A Block Bidiagonalization Method for Fixed-Accuracy Low-Rank Matrix Approximation (Q5863873) (← links)
- Randomized numerical linear algebra: Foundations and algorithms (Q5887823) (← links)
- Sparse matrices (Q5903172) (← links)
- A CCBM-based generalized GKB iterative regularization algorithm for inverse Cauchy problems (Q6175190) (← links)
