On statistical fuzzy trigonometric Korovkin theory

Abstract

In this study, we use regular matrix transformations in the approximation by fuzzy positive linear operators, where the test functions are trigonometric. So we prove a trigonometric fuzzy Korovkin theorem by means of A-statistical convergence, where A is a non-negative regular summability matrix. We also study rates of A-statistical convergence of a sequence of fuzzy positive linear operators in the trigonometric environment.