Classification with neural networks

  • A. Müller
  • J. Neumann
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


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.


Neural Network Test Pattern Sensorineural Hearing Loss Associative Memory Hide Unit 
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Copyright information

© Springer-Verlag Berlin · Heidelberg 1991

Authors and Affiliations

  • A. Müller
    • 1
    • 2
  • J. Neumann
    • 1
    • 2
  1. 1.Institut für Wirtschafts- und SozialpsychologieUniversität GöttingenGöttingenGermany
  2. 2.III. Physikalisches InstitutUniversität GöttingenGöttingenGermany

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