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Revista Colombiana de Matemáticas
versão impressa ISSN 0034-7426
Resumo
ANASTASSIOU, GEORGE A.. Voronovskaya Type Asymptotic Expansions for Error Function Based Quasi-Interpolation Neural Network Operators. Rev.colomb.mat. [online]. 2015, vol.49, n.1, pp.171-192. ISSN 0034-7426. https://doi.org/10.15446/recolma.v49n1.54179.
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.
Palavras-chave : Neural Network Fractional Approximation; Multivariate Neural Network Approximation; Voronovskaya AsymptoticExpansions; Fractional derivative; Error function.