A time-frequency approach for EEG signal segmentation

@inproceedings{Azarbad2014ATA,
  title={A time-frequency approach for EEG signal segmentation},
  author={Milad Azarbad and Hamed Azami and Saeid Sanei and Ataollah Ebrahimzadeh},
  year={2014}
}
The record of human brain neural activities, namely electroencephalogram (EEG), is known to be nonstationary in general. In addition, the human head is a non-linear medium for such signals. In many applications, it is useful to divide the EEGs into segments in which the signals can be considered stationary. Here, Hilbert-Huang Transform (HHT), as an effective tool in signal processing is applied since unlike the traditional time-frequency approaches, it exploits the non-linearity of the medium… CONTINUE READING

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