Paraconsistent logic approach for active noise reduction

Abstract

The Active Noise Reduction (ANR) is widely used in aircraft, headsets, telecommunications and medicine systems, to reduce or eliminate noise, while maintaining the characteristics of the desired signal. In this article a network of paraconsistent artificial neural cells (PANC) will be presented, based on the paraconsistent annotated logic by 2 values annotations (PAL2v) that allows to operate as ANR. Simulations indicate that the results presented by ANRPAL are better than those obtained by classic filters.

References

ABE, J. M. Paraconsistent artificial neural networks: An introduction. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2004.

ASLAM, M. S.; SHI, P.; LIM, C. C. Robust Active Noise Control Design by Optimal Weighted Least Squares Approach. IEEE Transactions on Circuits and Systems I: Regular Papers, 2019.

CARVALHO JUNIOR, A.; DA SILVA FILHO, J. I.; MARIO, M. C. Estimador de Estado Adaptativo Paraconsistente. Exatas Online, v. 9, p. 25–30, 2018 (portuguese).

CARVALHO JUNIOR, A. et al. A Study of Paraconsistent Artificial Neural Cell of Learning Applied as PAL2v Filter. IEEE Latin America Transactions, 2018.

COELHO, M. S. et al. Hybrid PI controller constructed with paraconsistent annotated logic. Control Engineering Practice, 2019.

KUO, S. M.; MORGAN, D. R. Active noise control: a tutorial review. Proceedings of the IEEE, 1999.

MINICZ, M. F.; MATUCK, G. R.; TASINAFFO, P. M.; DA SILVA FILHO, J. I. Célula Neural Artificial Paraconsistente de Aprendizagem por Extração do Efeito da Contradição. Revista Seleção Documental, p. 3–9, 2014 (portuguese). Available at: https://www.researchgate.net/publication/294259986_Celula_Neural_Artificial_Paraconsistente_de_Aprendizagem_por_Extracao_do_Efeito_da_Contradicao.
Published
2020-05-04
How to Cite
DE CARVALHO JUNIOR, Arnaldo et al. Paraconsistent logic approach for active noise reduction. Journal of Mechatronics Engineering, [S.l.], v. 3, n. 1, p. 2 - 8, may 2020. ISSN 2595-3230. Available at: <http://jme.ojs.galoa.net.br/index.php/jme/article/view/81>. Date accessed: 12 july 2020. doi: https://doi.org/10.21439/jme.v3i1.81.