Design of accurate formulas for approximating functions in weighted Hardy spaces by discrete energy minimization

Abstract

We propose a simple and effective method for designing approximation formulas for weighted analytic functions. We consider spaces of such functions according to weight functions expressing the decay properties of the functions. Then, we adopt the minimum worst error of the $n$-point approximation formulas in each space for characterizing the optimal sampling points for the approximation. In order to obtain approximately optimal sampling points, we consider minimization of a discrete energy related to the minimum worst error. Consequently, we obtain an approximation formula and its theoretical error estimate in each space. In addition, from some numerical experiments, we observe that the formula generated by the proposed method outperforms the corresponding formula derived with sinc approximation, which is near optimal in each space.

arXiv comment27 pages, 15 figures. The programs for the numerical computations in this article are available on https://github.com/KeTanakaN/mat_disc_ener_opt_approx

References in corpus (3)

• Distributing many points on spheres: minimal energy and designs
• Potential theoretic approach to design of accurate formulas for function approximation in symmetric weighted Hardy spaces
• An optimal approximation formula for functions with singularities

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