The cognitive technology of intelligent control: soft computing optimizer and deep machine learning

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.