Geodesic
Construction of a Logical-Algebraic Corrector for Increasing Adaptive Properties of the $\Sigma\Pi$-Neuron
Itogi nauki i tehniki. Sovremennaâ matematika i eë priloženiâ. Tematičeskie obzory, Proceedings of the International Conference “Actual Problems of Applied Mathematics and Physics,” Kabardino-Balkaria, Nalchik, May 17–21, 2017, Tome 154 (2018), pp. 81-88.

Voir la notice de l'article provenant de la source Math-Net.Ru

In this paper, we consider the problem of constructing a correction algorithm for increasing adaptive properties of the $\Sigma\Pi$-neuron, based solely on the structure of the $\Sigma\Pi$-neuron itself. The logical-algebraic method of data analysis is used for the construction of the corrector. Comparison of advantages of the neural-network approach and the logical-algebraic method leads to the conclusion that the combined approach to the organization of neural networks improves their efficiency and allows one to state rules that reveal hidden patterns in a given subject area and thus to improve the quality of the recognition system.
Mots-clés : $\Sigma\Pi$-neuron, classifier
Keywords: algorithm, corrector, predicate, disjunctive normal form, logical function. 
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L. A. Lyutikova. Construction of a Logical-Algebraic Corrector for Increasing Adaptive Properties of the $\Sigma\Pi$-Neuron. Itogi nauki i tehniki. Sovremennaâ matematika i eë priloženiâ. Tematičeskie obzory, Proceedings of the International Conference “Actual Problems of Applied Mathematics and Physics,” Kabardino-Balkaria, Nalchik, May 17–21, 2017, Tome 154 (2018), pp. 81-88. http://geodesic.mathdoc.fr/item/INTO_2018_154_a9/

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