Spectral condition‐number estimation of large sparse matrices-Reference-Cited by-同舟云学术

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Spectral condition‐number estimation of large sparse matrices

Published:2019-03-12 Issue:3 Volume:26 Page:
ISSN:1070-5325
Container-title:Numerical Linear Algebra with Applications
language:en
Short-container-title:Numer Linear Algebra Appl

Author:

Avron Haim¹^ORCID,Druinsky Alex²,Toledo Sivan²

Affiliation:

1. School of Mathematical Sciences Tel Aviv University Tel Aviv Israel

2. School of Computer Science Tel Aviv University Tel Aviv Israel

Funder

Israel Science Foundation

United States-Israel Binational Science Foundation

Defense Advanced Research Projects Agency

Publisher

Wiley

Subject

Applied Mathematics,Algebra and Number Theory

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/nla.2235

Reference33 articles.

1. Probabilistic Bounds for the Matrix Condition Number with Extended Lanczos Bidiagonalization

2. Using cross-product matrices to compute the SVD

3. ARPACK Users' Guide

4. Estimating the Largest Eigenvalue by the Power and Lanczos Algorithms with a Random Start

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1. Extreme singular values of inhomogeneous sparse random rectangular matrices;Bernoulli;2024-11-01

2. Accelerating Restarted GMRES With Mixed Precision Arithmetic;IEEE Transactions on Parallel and Distributed Systems;2022-04-01

3. A functional oriented truncation error adaptation method;Journal of Computational Physics;2022-02

4. Invertibility Conditions for the Admittance Matrices of Balanced Power Systems;IEEE Transactions on Power Systems;2022

5. On choices of formulations of computing the generalized singular value decomposition of a large matrix pair;Numerical Algorithms;2020-08-07

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