Research output: Contribution to journal › Conference article › peer-review
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.
Original language | English |
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Pages (from-to) | 128-133 |
Number of pages | 6 |
Journal | Procedia Computer Science |
Volume | 123 |
DOIs | |
State | Published - 1 Jan 2018 |
Event | 8th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2017 - Moscow, Russian Federation Duration: 1 Aug 2017 → 6 Aug 2017 |
ID: 36122212