Correlation Analysis of Nonstationary Data: Application to the Processing of EEG

An overview of the current achievements in the development of data processing approaches that provide a correlation analysis of non-stationary, short and noisy time series is given. The application of these tools to recognize specific patterns in multi-channel electroencephalograms (EEG) is consider...

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Bibliographic Details
Published in2018 2nd School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR) pp. 94 - 96
Main Author Pavlov, Alexey N.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2018
Subjects
Brain-computer interfaces
Correlation
correlation function
Data processing
detrended fluctuation analysis
Electroencephalography
Hurst exponent
Noise measurement
nonstationarity
signal processing
Time series analysis
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Summary:An overview of the current achievements in the development of data processing approaches that provide a correlation analysis of non-stationary, short and noisy time series is given. The application of these tools to recognize specific patterns in multi-channel electroencephalograms (EEG) is considered and the possibility of using correlation analysis in software for brain-computer interfaces is discussed.
DOI:10.1109/DCNAIR.2018.8589224