title: Parallel principal component neural networks for classification of event-related potential waveforms.
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.
authors.affiliation: Engineering Research Institute, University of Iceland, Reykjavik, Iceland.
authors.forename: J R
authors.initials: JR
authors.lastname: Sveinsson
authors.forename: J A
authors.initials: JA
authors.lastname: Benediktsson
authors.forename: S B
authors.initials: SB
authors.lastname: Stefansson
authors.forename: K
authors.initials: K
authors.lastname: Davidsson
mesh_terms: D000328:Adult; D001698:Biomedical Engineering; D005069:Evaluation Studies as Topic; D016057:Evoked Potentials, Auditory, Brain Stem / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D012559:Schizophrenia / Q000503:physiopathology