Title: Paraconsistent artificial neural networks and EEG analysis

Authors: Jair Minoro Abe, Helder Frederico da Silva Lopes, Renato Anghinah

Addresses: Graduate Program in Production Engineering, ICET, Paulista University, Sao Paulo, Brazil; Institute for Advanced Studies, University of Sao Paulo, Brazil. ' Faculty of Medicine, University of Sao Paulo, Brazil. ' Reference Center of Behavioral Disturbances and Dementia (CEREDIC) of Medicine School, University of Sao Paulo, Brazil

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

Keywords: artificial neural networks; paraconsistent ANNs; paraconsistent logic; annotated logic; pattern recognition; child dyslexia; brain EEG analysis; electroencephalographs; evidential logic; brain electrical activity; brainwaves; children.

DOI: 10.1504/IJRIS.2011.042266

International Journal of Reasoning-based Intelligent Systems, 2011 Vol.3 No.2, pp.115 - 123

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 02 Sep 2011 *

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