Paraconsistent artificial neural networks and EEG analysis

Authors:
Jair Minoro Abe;Helder F. S. Lopes;Kazumi Nakamatsu;Seiki Akama
Affiliations:
Graduate Program in Production Engineering, ICET, Paulista University, São Paulo, SP, Brazil 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, University of Hyogo, Japan;-
Venue:
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part III
Year:
2010

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Classification of EEG Recordings by Using Fast Independent Component Analysis and Artificial Neural Network

Journal of Medical Systems

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Abstract

The aim of this paper is to present a study of brain EEG waves through a new ANN based on Paraconsistent Annotated Evidential Logic Eτ which is capable of manipulating concepts like impreciseness, inconsistency, and paracompleteness in a nontrivial manner. As application, the Paraconsistent Artificial Neural Network - PANN showed capable of recognizing children with Dyslexia with Kappa index at a rate of 80%.