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Proceedings Paper

Patterns recognition of electric brain activity using artificial neural networks
Author(s): V. Yu. Musatov; S. V. Pchelintseva; A. E. Runnova; A. E. Hramov
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Paper Abstract

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Paper Details

Date Published: 14 April 2017
PDF: 7 pages
Proc. SPIE 10337, Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III, 1033714 (14 April 2017); doi: 10.1117/12.2267701
Show Author Affiliations
V. Yu. Musatov, Saratov State Technical Univ. (Russian Federation)
S. V. Pchelintseva, Saratov State Technical Univ. (Russian Federation)
A. E. Runnova, Saratov State Technical Univ. (Russian Federation)
A. E. Hramov, Saratov State Technical Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 10337:
Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III
Vladimir L. Derbov; Vladimir L. Derbov; Dmitry Engelevich Postnov; Dmitry Engelevich Postnov, Editor(s)

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