Adaptive filtering and analysis of EEG signals in the time-frequency domain based on the local entropy

Adaptive filtering and analysis of EEG signals in the time-frequency domain based on the local entropy

Abstract The brain dynamics in the electroencephalogram (EEG) data are often challenging to interpret, specially when the signal is a combination of desired brain dynamics and noise. Thus, in an EEG signal, anything other than the desired electrical activity, which is produced due to coordinated ele...

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Bibliographic Details
Main Authors: Guruprasad Madhale Jadav, Jonatan Lerga, Ivan Štajduhar
Format: Article
Language:English
Published: SpringerOpen 2020-02-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Non-stationary signals
Electroencephalogram (EEG)
Event-related potentials (ERP)
P300
Relative intersection of confidence interval (RICI)
Time-frequency signal analysis
Online Access:http://link.springer.com/article/10.1186/s13634-020-00667-6

Internet

http://link.springer.com/article/10.1186/s13634-020-00667-6

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