Quantitative Approximation by Kantorovich-Choquet quasi-interpolation neural network operators

Abstract

In this article we present univariate and multivariate basic approximation by Kantorovich-Choquet type quasi-interpolation neural networkoperators with respect to supremum norm. This is done with rates using the rst univariate and multivariate moduli of continuity. We approximate continuous and bounded functions on R^N; N \subset N. When they arealso uniformly continuous we have pointwise and uniform convergences.