"Approximating the generalized singular value expansion" by Mark Gockenbach and Matthew J. Roberts
 

Document Type

Article

Publication Date

9-11-2018

Abstract

The generalized singular value expansion (GSVE) simultaneously diagonalizes a pair of operators on Hilbert space. From a theoretical point of view, the GSVE enables a straightforward analysis of, for example, weighted least-squares problems and the method of Tikhonov regularization with seminorms. When the operators are discretized, an approximate GSVE can be computed from the generalized singular value decomposition of a pair of Galerkin matrices. Unless the discretization is carefully chosen, spurious modes can appear, but a natural condition on the discretization guarantees convergence of the approximate GSVE to the exact one. Numerical examples illustrate the pitfalls of a poor discretization and efficacy of the convergence conditions.

Publisher's Statement

Copyright 2018 Society for Industrial and Applied Mathematics. Article deposited here in compliance with publisher policy. Publisher's version of record: https://doi.org/10.1137/18M1163713

Publication Title

SIAM Journal on Numerical Analysis

Version

Publisher's PDF

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