Quantitative Approximation by a Kantorovich-Shilkret quasi-interpolation neural network operator

Abstract

In this article we present multivariate basic approximation by a Kantorovich-Shilkret type quasi-interpolation neural network operator with respect to supremum norm. This is done with rates using the multivariate modulus of continuity. We approximate continuous and bounded functions on ℝN, N ∈ ℕ. When they are additionally uniformly continuous we derive pointwise and uniform convergences.