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Brain states recognition during visual perception by means of artificial neural network in the different EEG frequency ranges
Author(s): V. Yu. Musatov; A. E. Runnova; A. V. Andreev; M. O. Zhuravlev
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Paper Abstract

In the present paper, the possibility of classification by artificial neural networks of a certain architecture of ambiguous images is investigated using the example of the Necker cube from the experimentally obtained EEG recording data of several operators. The possibilities of artificial neural network classification of ambiguous images are investigated in the different frequency ranges of EEG recording signals.

Paper Details

Date Published: 26 April 2018
PDF: 6 pages
Proc. SPIE 10717, Saratov Fall Meeting 2017: Laser Physics and Photonics XVIII; and Computational Biophysics and Analysis of Biomedical Data IV, 107171O (26 April 2018); doi: 10.1117/12.2314829
Show Author Affiliations
V. Yu. Musatov, Yuri Gagarin State Technical Univ. of Saratov (Russian Federation)
A. E. Runnova, Yuri Gagarin State Technical Univ. of Saratov (Russian Federation)
A. V. Andreev, Yuri Gagarin State Technical Univ. of Saratov (Russian Federation)
M. O. Zhuravlev, Yuri Gagarin State Technical Univ. of Saratov (Russian Federation)


Published in SPIE Proceedings Vol. 10717:
Saratov Fall Meeting 2017: Laser Physics and Photonics XVIII; and Computational Biophysics and Analysis of Biomedical Data IV
Vladimir L. Derbov; Dmitry Engelevich Postnov, Editor(s)

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