GPU-based high-performance computing of multichannel EEG phase wavelet synchronization

Alexander Efitorov, Irina Knyazeva, Boytsova Yulia, Sergey Danko

Результат исследований: Научные публикации в периодических изданияхстатья в журнале по материалам конференции

4 Цитирования (Scopus)

Выдержка

The work is devoted to GPU-based high performance realization of algorithm for wavelet phase synchronization. Wavelet phase coherence was applied for analyzing brain activity in states with different degrees of mental and sensory attention. In the analysis of electroencephalographic correlates of mental states, as a rule the focus is on the analysis of the spectral power of a quasi-stationary EEG or task-related power of time-frequency EEG spectra. The analysis of the wavelet phase coherence provides additional information on the organization of brain activity, but requires more computing time. Fast implementation can simplify the use of this method in practice.

Язык оригиналаанглийский
Страницы (с-по)128-133
Число страниц6
ЖурналProcedia Computer Science
Том123
DOI
СостояниеОпубликовано - 1 янв 2018
Событие8th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2017 - Moscow, Российская Федерация
Продолжительность: 1 авг 20176 авг 2017

Отпечаток

Electroencephalography
Brain
Synchronization
Graphics processing unit

Предметные области Scopus

  • Компьютерные науки (все)

Цитировать

Efitorov, Alexander ; Knyazeva, Irina ; Yulia, Boytsova ; Danko, Sergey. / GPU-based high-performance computing of multichannel EEG phase wavelet synchronization. В: Procedia Computer Science. 2018 ; Том 123. стр. 128-133.
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GPU-based high-performance computing of multichannel EEG phase wavelet synchronization. / Efitorov, Alexander; Knyazeva, Irina; Yulia, Boytsova; Danko, Sergey.

В: Procedia Computer Science, Том 123, 01.01.2018, стр. 128-133.

Результат исследований: Научные публикации в периодических изданияхстатья в журнале по материалам конференции

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