Paraconsistent Artificial Neural Cells (PANC)

PANCb (basic), PANCs (standard), PANCslc_max (OR - maximum input selected), PANCslc_min(AND - minimum input selected), PANCL and PANCLctx

The files in attach are the Paraconsistent Artificial Neural Cells (PANC) blocks for Simulink.

• PANCb: basic PANC with PAL2v rules
• PANCs: standard PANC with PAL2v rules, FtC and FtCT adjustes, built as matlab function
• PANCslc-max: select the higher input (Mi or Lambda)
• PANCslc-min: select the lower input (Mi or Lambda)
• PANCL: PANC of learning
• PANCLctx: PANC of learning with contradiction extraction

These PAL2v cells where inspired in the following references with applications:

[1] J. I. Da Silva Filho, G. Lambert-Torres, Germano J. M. Abe. (2010). Uncertainty treatment using paraconsistent logic: introducing paraconsistent artificial neural networks. IOS Press. ISBN: 978-1-60750-557-0.

[2] A. De Carvalho, Jr., J. I. Da Silva Filho, M. C. Mario, M. F. Blos and C. M. da Cruz, "A Study of Paraconsistent Artificial Neural Cell of Learning Applied as PAL2v Filter," in IEEE Latin America Transactions, vol. 16, no. 1, pp. 202-209, Jan. 2018, doi: 10.1109/TLA.2018.8291474.

[3] A. Carvalho, J. F. Justo, B. A. Angélico, et al. Paraconsistent State Estimator for a Furuta Pendulum Control. SN COMPUT. SCI. 4, 29 (2023). https://doi.org/10.1007/s42979-022-01427-z.

[4] A. Carvalho, et al. Paraconsistent logic approach for active noise reduction. Journal of Mechatronic Engineering. 2020;3(1):2–8.

[5] Da Silva Filho, J.I.; Fernandes, C.L.M.; Silveira, R.S.d.; Gomes, P.M.; Matos, S.L.d.C.; Santo, L.d.E.; Nunes, V.C.; Côrtes, H.M.; Lopes, W.A.C.; Mario, M.C.; Garcia, D.V.; Torres, C.R.; Abe, J.M.; Lambert-Torres, G. Process of Learning from Demonstration with Paraconsistent Artificial Neural Cells for Application in Linear Cartesian Robots. Robotics 2023, 12, 69. https://doi.org/10.3390/robotics12030069.