卷积算子序列对连续函数的AJ统计逼近

IF 1 Q1 MATHEMATICS

Kragujevac Journal of Mathematics Pub Date : 2022-06-01 DOI:10.46793/kgjmat2203.355d

S. Dutta, Rima Ghosh

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引用次数: 0

摘要

在本文中，根据Savas等人[22]引入的实序列的AI统计收敛概念，我们处理了定义在C[a，b]上的正卷积算子序列的Korovkin型逼近理论，C[a、b]上所有实值连续函数的空间，在Duman[6]的行中。在第3节中，我们研究了人工智能统计收敛的速度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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AJ-Statistical Approximation of Continuous Functions by Sequence of Convolution Operators

In this paper, following the concept of AI-statistical convergence for real sequences introduced by Savas et al. [22], we deal with Korovkin type approximation theory for a sequence of positive convolution operators defined on C[a, b], the space of all real valued continuous functions on [a, b], in the line of Duman [6]. In the Section 3, we study the rate of AI-statistical convergence.

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来源期刊

Kragujevac Journal of Mathematics MATHEMATICS-

CiteScore

2.50

自引率

0.00%

发文量