Year: 2024
Type: article
Abstract: The iterative rational Krylov algorithm (IRKA) is a commonly used fixed point iteration developed to minimize the$\mathcal {H}_{2}$model order reduction error. In this work, the IRKA is recast as a Riemannian gradient descent method with a fixed step size over the manifold of rational functions having fixed degree. This interpretation motivates the development of a Riemannian gradient descent method utilizing as a natural extension variable step size and line search. Comparisons made between the IRKA and this extension on a few examples demonstrate significant benefits.
Institutions: Virginia Tech, University of Zagreb
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4403936660