Equi-Statistical Relative Convergence and Korovkin-Type Approximation
Abstract
Classical approximation theory has started with the proof of Weierstrass approximation theorem and after that Korovkin [Linear operators and approximation theory, Hindustan Publ. Corp, Delhi, 1960] first established the necessary and sufficient conditions for uniform convergence of a sequence of positive linear operators to a function f . In classical Korovkin theorem, most of the classical operators tend to converge to the value of the function being approximated. Also, the attention of researchers has been attracted to the notion of statistical convergence because of the fact that it is stronger than the classical convergence method. Furthermore, the concept of equi-statistical convergence is more general than the statistical uniform convergence. In this work, we introduce our new convergence method named equi-statistical relative convergence to demonstrate a Korovkin type approximation theorems which were proven by earlier authors. Finally, we present an example in support of our definition and result presented in this paper.
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Cite this article
Yıldız, S., Demirci, K., & Dirik, F. (2019). Equi-Statistical Relative Convergence and Korovkin-Type Approximation. In 4th International Symposium on Innovative Approaches in Engineering and Natural Sciences (pp. 193–196). SET Technology. https://doi.org/10.36287/setsci.4.6.056
Article History
- Published
- 22 Dec 2019
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© 2019 SET Technology. This article is distributed under the terms of the CC BY 4.0.