Voronovskaya type asymptotic expansions for error function based quasi-interpolation neural network operators

Abstract

Here we examine the quasi-interpolation error function based neural network operators of one hidden layer. Based on fractional calculus theory we derive a fractional Voronovskaya type asymptotic expansion for the error of approximation of these operators to the unit operator, as we are studying the univariate case. We treat also analogously the multivariate case.

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Revista Colombiana de Matematicas

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