Classification with neural networks

In the fields of artificial intelligence, cognitive psychology, neurophysiology, and informatics in recent times neural networks have received a great deal of attention. Some general properties of these systems are discussed and exemplified in applications. The models used are a HOPFIELD-network and the BACKPROPAGATION learning algorithm. The latter is applied in the otological classification of persons regarding evoked otoacoustic emissions of normal or diseased ears, resp. The results show, that up to 71.1% are correctly classified. Classificatory abilities of neural networks, problems of preprocessing of spectral data and their analysis by backpropagation are discussed. Finally, there will be a short comparison between (higher order) associative memories and discriminant analysis.

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