Quantitative Approximation by a Kantorovich-Shilkret quasi-interpolation neural network operator
DOI:
https://doi.org/10.4067/S0719-06462018000300001Keywords:
error function based activation function, multivariate quasi-interpolation neural network approximation, Kantorovich-Shilkret type operatorAbstract
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 â„N, N ∈ â„•. When they are additionally uniformly continuous we derive pointwise and uniform convergences.
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