Classification by neural networks of evoked potentials. A first case study

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.