Approximation by Kantorovich-type max-min operators and its applications

Türkan Yeliz Gökçer and İsmail Aslan

Applied Mathematics and Computation, 2022, vol. 423, issue C

Abstract: In this study, we construct Kantorovich variant of max-min kind operators, which are nonlinear. By using these new operators, we obtain some uniform approximation results in N-dimension (N≥1). Then, we estimate the error with the help of Hölder continuous functions and modulus of continuity. Furthermore, we give some illustrative applications to verify our theory and also investigate some shape-preserving properties of Kantorovich-type max-min Bernstein operator. Lastly, we examine the image processing implementation of our results via Kantorovich-type max-min Shepard operator.

Keywords: Max-min operators; Kantorovich operators; Rate of approximation; Shape-preserving properties; Fuzzy logic; Image processing (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:423:y:2022:i:c:s0096300322000972

DOI: 10.1016/j.amc.2022.127011

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