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Time-frequency analysis of scalp eeg based on hilbert - huang transform
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Electroencephalography (EEG) is the electrical activity of the human brain and thus plays an important role to understand the cognitive function in neuroscience and clinical settings. However, the conventional EEG analyses based on the linear assumption usually are limited to analyzing the nonlinear waveform of brain signals. To address this issue, we present a datadriven method for analyzing scalp EEG signals in the timefrequency domain. Results from both simulation and resting EEG demonstrated
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