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dc.contributor.authorCardaliaguet, Pierre
dc.contributor.authorEuvrard, Guillaume
dc.date.accessioned2014-12-18T08:39:41Z
dc.date.available2014-12-18T08:39:41Z
dc.date.issued1992
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/14468
dc.language.isoenen
dc.subjectFeedforward neural networksen
dc.subjectFunctions approximationen
dc.subjectInterpolationen
dc.subjectBell-shaped functionsen
dc.subjectSquashing functionsen
dc.subjectRobustness with respect to noiseen
dc.subjectImplicit functionen
dc.subjectControlen
dc.subject.ddc515en
dc.titleApproximation of a function and its derivative with a neural networken
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenThis paper deals with the approximation of both a function and its derivative by feedforward neural networks. We propose an explicit formula of approximation which is noise resistant and can be easily modified with the patterns. We apply these results to approach a function defined implicitly, which is useful in control theory.en
dc.relation.isversionofjnlnameNeural Networks
dc.relation.isversionofjnlvol5en
dc.relation.isversionofjnlissue2en
dc.relation.isversionofjnldate1992
dc.relation.isversionofjnlpages207-220en
dc.relation.isversionofdoihttp://dx.doi.org/10.1016/S0893-6080(05)80020-6en
dc.relation.isversionofjnlpublisherElsevieren
dc.subject.ddclabelAnalyseen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen


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