Abstract
In the present paper, we introduce the notion of relatively uniform weighted summability and its statistical version based upon fractional-order difference operators of functions. The concept of relatively uniform weighted \(\alpha \beta \)-statistical convergence is also introduced and some inclusion relations concerning the newly proposed methods are derived. As an application, we prove a general Korovkin-type approximation theorem for functions of two variables and also construct an illustrative example by the help of generating function type non-tensor Meyer-König and Zeller operators. Moreover, it is shown that the proposed methods are non-trivial generalizations of relatively uniform convergence which includes a scale function. We estimate the rate of convergence of approximating positive linear operators by means of the modulus of continuity and give a Voronovskaja-type approximation theorem. Finally, we present some computational results and geometrical interpretations to illustrate some of our approximation results.
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Communicated by Rosihan M. Ali.
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Kadak, U., Srivastava, H.M. & Mursaleen, M. Relatively Uniform Weighted Summability Based on Fractional-Order Difference Operator. Bull. Malays. Math. Sci. Soc. 42, 2453–2480 (2019). https://doi.org/10.1007/s40840-018-0612-2
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DOI: https://doi.org/10.1007/s40840-018-0612-2
Keywords
- Weighted statistical convergence and weighted statistical summability
- Fractional-order difference operators of functions
- Relatively uniform convergence
- The rates of convergence
- Korovkin- and Voronovskaja-type approximation theorems