Geodesic
Theorem of training for a~competition algorithm
Sibirskij žurnal vyčislitelʹnoj matematiki, Tome 16 (2013) no. 1, pp. 1-9

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This paper is an extension of [1], where a new decision algorithm was proposed. In its operation, the unit resembles artificial neural networks. However the functioning of the algorithm proposed is based on the different concepts. It does not use the concept of a net, a neuron. The theorem of training for the new competition algorithm is proved. 
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     author = {V. S. Antyufeev},
     title = {Theorem of training for a~competition algorithm},
     journal = {Sibirskij \v{z}urnal vy\v{c}islitelʹnoj matematiki},
     pages = {1--9},
     publisher = {mathdoc},
     volume = {16},
     number = {1},
     year = {2013},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/SJVM_2013_16_1_a0/}
}
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V. S. Antyufeev. Theorem of training for a~competition algorithm. Sibirskij žurnal vyčislitelʹnoj matematiki, Tome 16 (2013) no. 1, pp. 1-9. http://geodesic.mathdoc.fr/item/SJVM_2013_16_1_a0/