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Statistical convergence of bivariate generalized bernstein operators via four-dimensional infinite matrices

Faruk Özger, Khursheed J‎. ‎Ansari

2022Filomat17 citationsDOIOpen Access PDF

Abstract

Our main aim in this work is to construct an original extension of bivariate Bernstein type operators based on multiple shape parameters to give an application of four-dimensional infinite matrices to approximation theory, and prove some Korovkin theorems using two summability methods: a statistical convergence method which is stronger than the classical case and a power series method. We obtain the rate of generalized statistical convergence, and the rate of convergence for the power series method. Moreover, we provide some computer graphics to numerically analyze the efficiency and accuracy of convergence of our operators and obtain corresponding error plots. All the results that have been obtained in the present paper can be extended to the case of n-variate functions.

Topics & Concepts

MathematicsBivariate analysisRate of convergenceConvergence (economics)Power seriesApplied mathematicsSeries (stratigraphy)Normal convergenceModes of convergence (annotated index)Convergence testsRandom variateExtension (predicate logic)Pure mathematicsMathematical analysisRandom variableStatisticsComputer scienceTopological spaceTopological vector spaceProgramming languageIsolated pointChannel (broadcasting)Economic growthPaleontologyComputer networkBiologyEconomicsApproximation Theory and Sequence SpacesMathematical Approximation and IntegrationIterative Methods for Nonlinear Equations