Approximation for $q$-Chlodowsky Operators via Statistical Convergence with Respect to Power Series Method

Halime Taşer; Tuğba Yurdakadim

doi:10.36753/mathenot.992220

EN

Approximation for $q$-Chlodowsky Operators via Statistical Convergence with Respect to Power Series Method

Abstract

Many results which are obtained or unable to obtained by classical calculus have also been studied by q-calculus. It is effective to use q-calculus since it acts as a bridge between mathematics and physics. The q-analog of Chlodowsky operators has been introduced and the approximation properties of these operators have been studied in [12]. Then in [23], the q-analog of Stancu-Chlodowsky operators has been introduced and some approximation results of these operators have been studied via A-statistical convergence which is a more general setting.In this paper, we present the approximation properties of q-Chlodowsky operators via statistical convergence with respect to power series method. It is noteworthy to mention that statistical convergence and statistical convergence with respect to power series method are incompatible.

Keywords

q-calculus, Chlodowsky operators, approximation theory, power series method, statistical convergence

References

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Details

Primary Language

English

Subjects

Mathematical Sciences

Journal Section

Research Article

Authors

Halime Taşer ^*
0000-0003-2338-9242
Türkiye

Tuğba Yurdakadim
0000-0003-2522-6092
Türkiye

Publication Date

June 1, 2022

Submission Date

September 7, 2021

Acceptance Date

November 29, 2021

Published in Issue

Year 2022 Volume: 10 Number: 2

DOI

https://doi.org/10.36753/mathenot.992220

IZ

https://izlik.org/JA85LB92JC

APA

Taşer, H., & Yurdakadim, T. (2022). Approximation for $q$-Chlodowsky Operators via Statistical Convergence with Respect to Power Series Method. Mathematical Sciences and Applications E-Notes, 10(2), 72-81. https://doi.org/10.36753/mathenot.992220

AMA

1.Taşer H, Yurdakadim T. Approximation for $q$-Chlodowsky Operators via Statistical Convergence with Respect to Power Series Method. Math. Sci. Appl. E-Notes. 2022;10(2):72-81. doi:10.36753/mathenot.992220

Chicago

Taşer, Halime, and Tuğba Yurdakadim. 2022. “Approximation for $q$-Chlodowsky Operators via Statistical Convergence With Respect to Power Series Method”. Mathematical Sciences and Applications E-Notes 10 (2): 72-81. https://doi.org/10.36753/mathenot.992220.

EndNote

Taşer H, Yurdakadim T (June 1, 2022) Approximation for $q$-Chlodowsky Operators via Statistical Convergence with Respect to Power Series Method. Mathematical Sciences and Applications E-Notes 10 2 72–81.

IEEE

[1]H. Taşer and T. Yurdakadim, “Approximation for $q$-Chlodowsky Operators via Statistical Convergence with Respect to Power Series Method”, Math. Sci. Appl. E-Notes, vol. 10, no. 2, pp. 72–81, June 2022, doi: 10.36753/mathenot.992220.

ISNAD

Taşer, Halime - Yurdakadim, Tuğba. “Approximation for $q$-Chlodowsky Operators via Statistical Convergence With Respect to Power Series Method”. Mathematical Sciences and Applications E-Notes 10/2 (June 1, 2022): 72-81. https://doi.org/10.36753/mathenot.992220.

JAMA

1.Taşer H, Yurdakadim T. Approximation for $q$-Chlodowsky Operators via Statistical Convergence with Respect to Power Series Method. Math. Sci. Appl. E-Notes. 2022;10:72–81.

MLA

Taşer, Halime, and Tuğba Yurdakadim. “Approximation for $q$-Chlodowsky Operators via Statistical Convergence With Respect to Power Series Method”. Mathematical Sciences and Applications E-Notes, vol. 10, no. 2, June 2022, pp. 72-81, doi:10.36753/mathenot.992220.

Vancouver

1.Halime Taşer, Tuğba Yurdakadim. Approximation for $q$-Chlodowsky Operators via Statistical Convergence with Respect to Power Series Method. Math. Sci. Appl. E-Notes. 2022 Jun. 1;10(2):72-81. doi:10.36753/mathenot.992220

Cited By

Approximation theorems via Pp -statistical convergence on weighted spaces

Mathematica Slovaca

https://doi.org/10.1515/ms-2024-0050

Blending type approximation of generalized Lupaş-Jain type operators via A-statistical convergence and power series method

Filomat

https://doi.org/10.2298/FIL2417017S

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