A Paraconsistent Artificial Neural Cell of Learning by Contradiction Extraction (PANCLCTX) with Application Examples

Paraconsistent logic (PL) allows decision-making systems to deal with uncertainty and contradictory signals offering an alternative to the classical logic. Using the interpretations and equations of the PL, it is possible to program blocks of codes called Paraconsistent Artificial Neural Cells (PANCs) used to design data processing systems through paraconsistent artificial neural networks (PANnets). Among the several types of paraconsistent cells, one of the most used is the Paraconsistent Artificial Neural Cell of learning (PANCL). In this chapter, we present a new form of the PANCL based on extraction of the contradiction effects between the input and the previous output, called PANCLCTX. The results presented here demonstrate that the proposed cell works effectively integrating asymptotic mode values, with practical applications for industry in signal analysis, estimation and treatment.