Improving EEG Analysis by Using Paraconsistent Artificial Neural Networks

Authors:
Jair Minoro Abe;Helder F. Lopes;Kazumi Nakamatsu
Affiliations:
Graduate Program in Production Engineering, ICET - Paulista University, São Paulo, Brazil CEP 04026-002 and Institute For Advanced Studies, University of São Paulo, Brazil;Institute For Advanced Studies, University of São Paulo, Brazil;School of Human Science and Environment/H.S.E., University of Hyogo, Japan
Venue:
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
Year:
2008

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Abstract

In this paper we present a study of EEG by using the Paraconsistent Artificial Neural Network --- PANN that can manipulate imprecise, contradictory and paracomplete data. Some improvements for EEG analysis are discussed. Experimental results concerning Alzheimer Disease made are also reported.