Please use this identifier to cite or link to this item: https://hdl.handle.net/10953/3181
Title: Approximation rate and saturation under generalized convergence
Authors: Garrancho, Pedro
Martínez-Sánchez, Francisco-Javier
Cárdenas-Morales, Daniel
Abstract: In this paper we prove a quantitative result about the convergence of sequences of functions de ned from linear operators. The notion of conver- gence used here is the one given in [8]. The operators will be assumed to satisfy a shape preserving property associated with certain generalized deriv- ative. We also study the saturation class, from the asymptotic condition that the sequence of operators ful lls. Finally, as applications, we show how the notion of weighted g-statistical convergence, recently studied by A. Adem and M. Altinok [3], can be moved to the setting of approximation theory. Besides, we give a non standard example that shows the applicability of the results.
Keywords: Korovkin-type results
Generalized convergence
Saturation class
Issue Date: Feb-2024
metadata.dc.description.sponsorship: This work is partially supported by the Spanish government Research Project PGC2018-097621-B-I00, and by Junta de Andalucía Research Group FQM-0178.
Publisher: American Institute of Mathematical Sciences
Citation: P. Garrancho, F.-J. Martínez-Sánchez, D. Cárdenas-Morales, Approximation rate and saturation under generalized convergence, Mathematical Foundations of Computing 2024, Volume 7, Issue 1: 148-157.
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