On statistical fuzzy trigonometric Korovkin theory
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. Copyright 2008 Eudoxus Press, LLC.
Journal of Computational Analysis and Applications
Duman, O., & Anastassiou, G. (2008). On statistical fuzzy trigonometric Korovkin theory. Journal of Computational Analysis and Applications, 10 (3), 333-344. Retrieved from https://digitalcommons.memphis.edu/facpubs/5319