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Approximation rate and saturation under generalized convergence

Fecha

2024-02

Título de la revista

ISSN de la revista

Título del volumen

Editor

American Institute of Mathematical Sciences

Resumen

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.

Descripción

This article has been published in a revised form in Mathematical Foundations of Computing http://dx.doi.org/10.3934/mfc.2023002. This version is free to download for private research and study only. Not for redistribution, re-sale or use in derivative works

Palabras clave

Korovkin-type results, Generalized convergence, Saturation class

Citación

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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