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Itogi Nauki i Tekhniki. Sovremennaya Matematika i ee Prilozheniya. Tematicheskie Obzory, 2018, Volume 154, Pages 43–48
(Mi into376)
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This article is cited in 3 scientific papers (total in 3 papers)
On a Method of Constructing Logical Neural Networks Based on Variable-Valued Logic Functions
D. P. Dimitrichenko, R. A. Zhilov Institute of Applied Mathematics and Automation, Nalchik
Abstract:
A method for constructing logical neural networks based on variable-valued logic functions is proposed. A theorem on the possibility of representing any logical function as a logical neural network is proved. The proof also contains an algorithm for constructing a logical neural network. The possibility of a generalization of the result obtained to the case of fuzzy logic is indicated.
Keywords:
variable-valued predicate, data mining, variable-valued logical function, training sample, neural network approach, logical neural network, fuzzy logic.
Citation:
D. P. Dimitrichenko, R. A. Zhilov, “On a Method of Constructing Logical Neural Networks Based on Variable-Valued Logic Functions”, Proceedings of the International Conference “Actual Problems of Applied Mathematics and Physics,” Kabardino-Balkaria, Nalchik, May 17–21, 2017, Itogi Nauki i Tekhniki. Sovrem. Mat. Pril. Temat. Obz., 154, VINITI, Moscow, 2018, 43–48; J. Math. Sci. (N. Y.), 253:4 (2021), 500–505
Linking options:
https://www.mathnet.ru/eng/into376 https://www.mathnet.ru/eng/into/v154/p43
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Abstract page: | 226 | Full-text PDF : | 254 | References: | 23 | First page: | 1 |
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