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

IF 1 Q1 MATHEMATICS
S. Dutta, Rima Ghosh
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引用次数: 0

Abstract

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.
卷积算子序列对连续函数的AJ统计逼近
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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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
50
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