title: Classification by neural networks of evoked potentials. A first case study.
abstract: This paper describes the application of artificial neural networks for the analysis of data of the evoked potential type. A discussion of different preprocessing schemes stresses the importance of a suitable method which supports the artificial neural networks in their classification task. This preprocessing differs completely from well-known data reduction methods used for non-neural classifiers. The examples shown here show the extraordinarily good tolerance against noise, yielding very good classification results for only a small number of observations.
authors.affiliation: Universität Kassel, FG Neuronale Netzwerke, BRD.
authors.forename: B
authors.initials: B
authors.lastname: Klöppel
mesh_terms: D000437:Alcoholism / Q000145:classification / Q000503:physiopathology; D004569:Electroencephalography; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D016571:Neural Networks, Computer