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dc.contributor.authorRieger, Ankede
dc.date.accessioned2004-12-06T12:53:26Z-
dc.date.available2004-12-06T12:53:26Z-
dc.date.created1993de
dc.date.issued1999-08-12de
dc.identifier.issn0943-4135de
dc.identifier.urihttp://hdl.handle.net/2003/2575-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-14886-
dc.description.abstractThe report gives an introduction to neural networks. Starting with the basic terminology, different types of neural networks are described. Several applications of neural networks are shown, e.g. pattern recognition, content-adressable memory, and optimization problems. The major part of the report is focused on learning. Methods for learning from examples as well as methods for learning from observations are described. This report has been used as part of a script for a graduate student course in AI. It aims at teaching the basics of neural networks with the intention to make accessible the mathematical techniques used in this context. The paper is written in German.en
dc.format.extent1275721 bytes-
dc.format.extent201863 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/postscript-
dc.language.isodede
dc.publisherUniversität Dortmundde
dc.relation.ispartofseriesForschungsberichte des Lehrstuhls VIII, Fachbereich Informatik der Universität Dortmund ; 2de
dc.subject.ddc004de
dc.titleNeuronale Netzwerkede
dc.typeTextde
dc.type.publicationtypereport-
dcterms.accessRightsopen access-
Appears in Collections:LS 08 Künstliche Intelligenz

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