Approximation rate and saturation under generalized convergence
Archivos
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.