Parallel principal component neural networks for classification of event-related potential waveforms

Johannes R. Sveinsson*, Jon Atli Benediktsson, Sigurjon B. Stefansson, Kari Davidsson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Artificial neural networks (ANNs) are discussed in terms of classification of brain auditory event-related potentials (ERPs). A new ANN architecture for the classification of ERPs is proposed. The new architecture is called the parallel principal component neural network (PPCNN). The use of the PPCNN for classification of ERP data obtained from both normal control subjects and chronic schizophrenic patients is discussed. Experimental results are given.

Original languageEnglish
Pages (from-to)15-20
Number of pages6
JournalMedical Engineering and Physics
Volume19
Issue number1
DOIs
Publication statusPublished - Jan 1997

Other keywords

  • Artificial neural networks
  • Auditory event-related potential
  • Classification
  • Schizophrenia

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