AbstractRecently, it has been shown that sum and product are not the only operations that can be used in order to define concrete approximation operators. Several other operations provided by fuzzy sets theory can be used. In the present paper, pseudo-linear approximation operators are investigated from the practical point of view in Image Processing. We study max–min, max–product Shepard type approximation operators together with Shepard operators based on pseudo-operations generated by an increasing continuous generator. It is shown that in several cases these outperform classical approximation operators based on sum and product operations
A Gupta-type variant of Shepard operators is introduced and convergence results and pointwise and un...
AbstractIn this paper, using the concept of statistical σ-convergence which is stronger than statist...
AbstractThe aim of this paper is to investigate the error which results from the method of approxima...
The approximation operators provided by classical approximation theory use exclusively as underlying...
The approximation operators provided by classical approximation theory use exclusively as underlying...
The approximation operators provided by classical Approximation Theory use ex-clusively as underlyin...
The approximation operators provided by classical approximation theory use exclusively as underlying...
First asymptotic relations of Voronovskaya-type for rational operators of Shepard-type are shown. A...
Here we study quantitatively the approximation of fuzzy numbers by fuzzy approximators generated by ...
Here we study quantitatively the approximation of fuzzy numbers by fuzzy approximators generated by ...
The main idea of statistical convergence is to demand convergence only for a majority of elements of...
Abstract A Gupta-type variant of Shepard operators is introduced and convergence results and pointwi...
In this paper, the fuzziness of Gomolińska approx-imation space based on uncertainty mappings was in...
In this study, we obtain a general approximation theorem for max-min operators including many signif...
In this paper, we consider the max-product neural network operators of the Kantorovich type based on...
A Gupta-type variant of Shepard operators is introduced and convergence results and pointwise and un...
AbstractIn this paper, using the concept of statistical σ-convergence which is stronger than statist...
AbstractThe aim of this paper is to investigate the error which results from the method of approxima...
The approximation operators provided by classical approximation theory use exclusively as underlying...
The approximation operators provided by classical approximation theory use exclusively as underlying...
The approximation operators provided by classical Approximation Theory use ex-clusively as underlyin...
The approximation operators provided by classical approximation theory use exclusively as underlying...
First asymptotic relations of Voronovskaya-type for rational operators of Shepard-type are shown. A...
Here we study quantitatively the approximation of fuzzy numbers by fuzzy approximators generated by ...
Here we study quantitatively the approximation of fuzzy numbers by fuzzy approximators generated by ...
The main idea of statistical convergence is to demand convergence only for a majority of elements of...
Abstract A Gupta-type variant of Shepard operators is introduced and convergence results and pointwi...
In this paper, the fuzziness of Gomolińska approx-imation space based on uncertainty mappings was in...
In this study, we obtain a general approximation theorem for max-min operators including many signif...
In this paper, we consider the max-product neural network operators of the Kantorovich type based on...
A Gupta-type variant of Shepard operators is introduced and convergence results and pointwise and un...
AbstractIn this paper, using the concept of statistical σ-convergence which is stronger than statist...
AbstractThe aim of this paper is to investigate the error which results from the method of approxima...