Low-Memory Krylov Subspace Methods for Optimal Rational Matrix Function Approximation-Reference-Cited by-同舟云学术

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Low-Memory Krylov Subspace Methods for Optimal Rational Matrix Function Approximation

Published:2023-05-19 Issue:2 Volume:44 Page:670-692
ISSN:0895-4798
Container-title:SIAM Journal on Matrix Analysis and Applications
language:en
Short-container-title:SIAM J. Matrix Anal. Appl.

Author:

Chen Tyler¹^ORCID,Greenbaum Anne²^ORCID,Musco Cameron³,Musco Christopher¹

Affiliation:

1. Tandon School of Engineering, New York University, Brooklyn, NY 11201 USA.

2. Applied Mathematics, University of Washington, Seattle, WA 98195 USA.

3. Manning College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA 01003 USA.

Funder

Adobe Systems

National Science Foundation

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Analysis

Reference35 articles.

1. Implementation of a restarted Krylov subspace method for the evaluation of matrix functions

2. Fast Methods for Computing the Neuberger Operator

3. Error Bounds for Lanczos-Based Matrix Function Approximation

4. Relations between Galerkin and Norm-Minimizing Iterative Methods for Solving Linear Systems

5. Using Nonorthogonal Lanczos Vectors in the Computation of Matrix Functions

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