Berljafa, Mario and Güttel, Stefan (2015) The RKFIT algorithm for nonlinear rational approximation. [MIMS Preprint]
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Abstract
The RKFIT algorithm outlined in [M. Berljafa and S. Güttel, Generalized rational Krylov decompositions with an application to rational approximation, SIAM J. Matrix Anal. Appl., 2015] is a Krylov-based approach for solving nonlinear rational least squares problems. This paper puts RKFIT into a general framework, allowing for its extension to nondiagonal rational approximants and a family of approximants sharing a common denominator. Furthermore, we derive a strategy for the degree reduction of the approximants, as well as methods for their conversion to partial fraction form, for the efficient evaluation, and root-finding. We also discuss commons and differences of RKFIT and the popular vector fitting algorithm. A MATLAB implementation of RKFIT is provided and numerical experiments, including the fitting of a MIMO dynamical system and an optimization problem related to exponential integration, demonstrate its applicability.
Item Type: | MIMS Preprint |
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Uncontrolled Keywords: | nonlinear rational approximation, least squares, rational Krylov method |
Subjects: | MSC 2010, the AMS's Mathematics Subject Classification > 41 Approximations and expansions MSC 2010, the AMS's Mathematics Subject Classification > 65 Numerical analysis |
Depositing User: | Stefan Güttel |
Date Deposited: | 10 Jun 2015 |
Last Modified: | 08 Nov 2017 18:18 |
URI: | https://eprints.maths.manchester.ac.uk/id/eprint/2309 |
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