Fractional Voronovskaya type asymptotic expansions for quasi-interpolation neural network operators

Here we study further the quasi-interpolation of sigmoidal and hyperbolic tangent types neural network operators of one hidden layer. Based on fractional calculus theory we derive fractional Voronovskaya type asymptotic expansions for the error of approximation of these operators to the unit operato...

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Autor principal:	Anastassiou,George A
Lenguaje:	English
Publicado:	Universidad de La Frontera. Departamento de Matemática y Estadística. 2012
Materias:	Neural Network Fractional Approximation Voro-novskaya Asymptotic Expansion fractional derivative
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0719-06462012000300005
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spelling	oai:scielo:S0719-064620120003000052018-10-08Fractional Voronovskaya type asymptotic expansions for quasi-interpolation neural network operatorsAnastassiou,George A Neural Network Fractional Approximation Voro-novskaya Asymptotic Expansion fractional derivative Here we study further the quasi-interpolation of sigmoidal and hyperbolic tangent types neural network operators of one hidden layer. Based on fractional calculus theory we derive fractional Voronovskaya type asymptotic expansions for the error of approximation of these operators to the unit operator.info:eu-repo/semantics/openAccessUniversidad de La Frontera. Departamento de Matemática y Estadística.Cubo (Temuco) v.14 n.3 20122012-10-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0719-06462012000300005en10.4067/S0719-06462012000300005
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Neural Network Fractional Approximation Voro-novskaya Asymptotic Expansion fractional derivative
spellingShingle	Neural Network Fractional Approximation Voro-novskaya Asymptotic Expansion fractional derivative Anastassiou,George A Fractional Voronovskaya type asymptotic expansions for quasi-interpolation neural network operators
description	Here we study further the quasi-interpolation of sigmoidal and hyperbolic tangent types neural network operators of one hidden layer. Based on fractional calculus theory we derive fractional Voronovskaya type asymptotic expansions for the error of approximation of these operators to the unit operator.
author	Anastassiou,George A
author_facet	Anastassiou,George A
author_sort	Anastassiou,George A
title	Fractional Voronovskaya type asymptotic expansions for quasi-interpolation neural network operators
title_short	Fractional Voronovskaya type asymptotic expansions for quasi-interpolation neural network operators
title_full	Fractional Voronovskaya type asymptotic expansions for quasi-interpolation neural network operators
title_fullStr	Fractional Voronovskaya type asymptotic expansions for quasi-interpolation neural network operators
title_full_unstemmed	Fractional Voronovskaya type asymptotic expansions for quasi-interpolation neural network operators
title_sort	fractional voronovskaya type asymptotic expansions for quasi-interpolation neural network operators
publisher	Universidad de La Frontera. Departamento de Matemática y Estadística.
publishDate	2012
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0719-06462012000300005
work_keys_str_mv	AT anastassiougeorgea fractionalvoronovskayatypeasymptoticexpansionsforquasiinterpolationneuralnetworkoperators
_version_	1714206779455307776

Fractional Voronovskaya type asymptotic expansions for quasi-interpolation neural network operators

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