AJ-Statistical Approximation of Continuous Functions by Sequence of Convolution Operators
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Authors: S. DUTTA AND R. GHOSH
DOI: 10.46793/KgJMat2203.355D
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.
Keywords:
Ideal, AJ-statistical convergence, positive linear operator, convolution
operator, Korovkin type approximation theorem, rate of convergence.
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