Interpolation constrained rational minimax approximation with barycentric representation

Fuente: arXiv
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Main Authors: Zhang, Lei-Hong, Zhang, Ya-Nan
Format: Preprint
Published: 2025
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author Zhang, Lei-Hong
Zhang, Ya-Nan
author_facet Zhang, Lei-Hong
Zhang, Ya-Nan
contents In this paper, we propose a novel dual-based Lawson's method, termed {b-d-Lawson}, designed for addressing the rational minimax approximation under specific interpolation conditions. The {b-d-Lawson} approach incorporates two pivotal components that have been recently gained prominence in the realm of the rational approximations: the barycentric representation of the rational function and the dual framework for tackling minimax approximation challenges. The employment of barycentric formulae enables a streamlined parameterization of the rational function, ensuring natural satisfaction of interpolation conditions while mitigating numerical instability typically associated with Vandermonde basis matrices when monomial bases are utilized. This enhances both the accuracy and computational stability of the method. To address the bi-level min-max structure, the dual framework effectively transforms the challenge into a max-min dual problem, thereby facilitating the efficient application of Lawson's iteration. The integration of this dual perspective is crucial for optimizing the approximation process. We will discuss several applications of interpolation-constrained rational minimax approximation and illustrate numerical results to evaluate the performance of the {b-d-Lawson} method.
format Preprint
id arxiv_https___arxiv_org_abs_2502_10665
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Interpolation constrained rational minimax approximation with barycentric representation
Zhang, Lei-Hong
Zhang, Ya-Nan
Numerical Analysis
41A50, 41A20, 65D15, 90C46
In this paper, we propose a novel dual-based Lawson's method, termed {b-d-Lawson}, designed for addressing the rational minimax approximation under specific interpolation conditions. The {b-d-Lawson} approach incorporates two pivotal components that have been recently gained prominence in the realm of the rational approximations: the barycentric representation of the rational function and the dual framework for tackling minimax approximation challenges. The employment of barycentric formulae enables a streamlined parameterization of the rational function, ensuring natural satisfaction of interpolation conditions while mitigating numerical instability typically associated with Vandermonde basis matrices when monomial bases are utilized. This enhances both the accuracy and computational stability of the method. To address the bi-level min-max structure, the dual framework effectively transforms the challenge into a max-min dual problem, thereby facilitating the efficient application of Lawson's iteration. The integration of this dual perspective is crucial for optimizing the approximation process. We will discuss several applications of interpolation-constrained rational minimax approximation and illustrate numerical results to evaluate the performance of the {b-d-Lawson} method.
title Interpolation constrained rational minimax approximation with barycentric representation
topic Numerical Analysis
41A50, 41A20, 65D15, 90C46
url https://arxiv.org/abs/2502.10665