Estimating the largest singular values of large sparse matrices via modified moments

DOI10.1007/BF02142380zbMath0757.65039OpenAlexW1999685728MaRDI QIDQ1186625

Gene H. Golub, Michael W. Berry

Publication date: 28 June 1992

Published in: Numerical Algorithms (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02142380

zbMATH Keywords

numerical examplessingular valuesparallel computersbidiagonal matriceslarge sparse matricesmodified momentsLanczos recursion

Mathematics Subject Classification ID

Computational methods for sparse matrices (65F50) Numerical computation of eigenvalues and eigenvectors of matrices (65F15)

Related Items (3)

Computation of the fundamental singular subspace of a large matrix ⋮ Low cost optimization techniques for solving the nonlinear seismic reflection tomography problem ⋮ Approximating dominant singular triplets of large sparse matrices via modified moments

Uses Software

• Harwell-Boeing sparse matrix collection

Cites Work

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• Chebyshev semi-iterative methods, successive overrelaxation iterative methods, and second order Richardson iterative methods. I, II
• Analysis of the symmetric Lanczos algorithm with reorthogonalization methods
• SYMMETRIC GAUGE FUNCTIONS AND UNITARILY INVARIANT NORMS
• Sparse matrix test problems
• Robust methods in inverse theory
• Estimates of Eigenvalues for Iterative Methods
• A Block Lanczos Method for Computing the Singular Values and Corresponding Singular Vectors of a Matrix
• On Generating Orthogonal Polynomials
• The Lanczos Algorithm with Selective Orthogonalization
• Calculating the Singular Values and Pseudo-Inverse of a Matrix
• Regularisation of nonlinear inverse problems: imaging the near-surface weathering layer

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