Geodesic
Application valued variable logic functions and neural networks in the decision-making system
Vestnik KRAUNC. Fiziko-matematičeskie nauki, no. 5 (2016), pp. 93-100

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In this paper we propose a method for representing various-valued logic function in a logical neural network. This logical neural network will keep the totality of cause-andeffect relationships identified using various-valued logic functions with-in a given specified area. Thus, it becomes possible to transfer a logical algorithm to detect hidden patterns in a given specified area, in case when the values of logical variables are not well-defined and are values obscured between zero and one. These logic operations are implemented by special logic neural cells: conjunctors and disjunctors.
Keywords: predicate, the predicate atomicity, various-valued logical function logical neural network, fuzzy logic variable. 
@article{VKAM_2016_5_a13,
     author = {D. P. Dimitrichenko},
     title = {Application valued variable logic functions and neural networks in the decision-making system},
     journal = {Vestnik KRAUNC. Fiziko-matemati\v{c}eskie nauki},
     pages = {93--100},
     publisher = {mathdoc},
     number = {5},
     year = {2016},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/VKAM_2016_5_a13/}
}
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D. P. Dimitrichenko. Application valued variable logic functions and neural networks in the decision-making system. Vestnik KRAUNC. Fiziko-matematičeskie nauki, no. 5 (2016), pp. 93-100. http://geodesic.mathdoc.fr/item/VKAM_2016_5_a13/