Geodesic
The cognitive technology of intelligent control: soft computing optimizer and deep machine learning
Nečetkie sistemy i mâgkie vyčisleniâ, Tome 13 (2018) no. 2, pp. 166-182

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The article discusses the possibility of using the deep machine learning technology based on the soft computing optimizer in cognitive intelligent control using a cognitive helmet as a neural interface. The goal of this work is to experimentally show the possibility of classifying the mental states of a human operator, to identify objective indicators of the psychophysiological state of the examined person. The role and necessity of applying intelligent calculations in the task of describing the general psychophysical state of an operator is shown with examples.
Keywords: neural interface, intelligent computing, intelligent control system, deep machine learning, emotions. 
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     author = {S. V. Ul'yanov and A. A. Mamaeva and A. V. Schevchenko},
     title = {The cognitive technology of intelligent control: soft computing optimizer and deep machine learning},
     journal = {Ne\v{c}etkie sistemy i m\^agkie vy\v{c}isleni\^a},
     pages = {166--182},
     publisher = {mathdoc},
     volume = {13},
     number = {2},
     year = {2018},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/FSSC_2018_13_2_a4/}
}
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S. V. Ul'yanov; A. A. Mamaeva; A. V. Schevchenko. The cognitive technology of intelligent control: soft computing optimizer and deep machine learning. Nečetkie sistemy i mâgkie vyčisleniâ, Tome 13 (2018) no. 2, pp. 166-182. http://geodesic.mathdoc.fr/item/FSSC_2018_13_2_a4/