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

dc.creatorAnastassiou, George A.
dc.date2012-10-01
dc.identifierhttps://revistas.ufro.cl/ojs/index.php/cubo/article/view/1332
dc.identifier10.4067/S0719-06462012000300005
dc.descriptionHere 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.en-US
dc.formatapplication/pdf
dc.languageeng
dc.publisherUniversidad de La Frontera. Temuco, Chile.en-US
dc.relationhttps://revistas.ufro.cl/ojs/index.php/cubo/article/view/1332/1187
dc.sourceCUBO, A Mathematical Journal; Vol. 14 No. 3 (2012): CUBO, A Mathematical Journal; 71–83en-US
dc.sourceCUBO, A Mathematical Journal; Vol. 14 Núm. 3 (2012): CUBO, A Mathematical Journal; 71–83es-ES
dc.source0719-0646
dc.source0716-7776
dc.subjectNeural Network Fractional Approximationen-US
dc.subjectVoro- novskaya Asymptotic Expansionen-US
dc.subjectfractional derivativeen-US
dc.titleFractional Voronovskaya type asymptotic expansions for quasi-interpolation neural network operatorsen-US
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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