TY - GEN
T1 - Study of inter-session variability of long term memory and complexity of EEG signals
AU - Chatterjee, Somsirsa
AU - Bhattacharyya, Saugat
AU - Khasnobish, Anwesha
AU - Konar, Amit
AU - Tibarewala, D. N.
AU - Janarthanan, R.
PY - 2013/1/11
Y1 - 2013/1/11
N2 - Hurst exponent is used to evaluate the presence or absence of long-range dependence and its degree in a time series, and hence is known as the long term memory of the time series. Fractal Dimension on the other hand is a measure of data complexity. Hurst Exponent and Fractal Dimension were used as features for nonlinear classification by QDA and SVM with a polynomial kernel of order 3. Since both Hurst Exponent and Fractal Dimension has a large inter individual variability, we used these features of consecutive sessions to study the intersession variability of classification accuracy of the proposed classifiers. QDA provided better classification for the trials trained by motor execution, while SVM with the polynomial kernel differentiated better when the training was done by motor imagery data.
AB - Hurst exponent is used to evaluate the presence or absence of long-range dependence and its degree in a time series, and hence is known as the long term memory of the time series. Fractal Dimension on the other hand is a measure of data complexity. Hurst Exponent and Fractal Dimension were used as features for nonlinear classification by QDA and SVM with a polynomial kernel of order 3. Since both Hurst Exponent and Fractal Dimension has a large inter individual variability, we used these features of consecutive sessions to study the intersession variability of classification accuracy of the proposed classifiers. QDA provided better classification for the trials trained by motor execution, while SVM with the polynomial kernel differentiated better when the training was done by motor imagery data.
KW - Fractal Dimension
KW - Hurst Exponent
KW - Intersession variability
KW - polynomial kernel
KW - QDA
KW - SVM
UR - http://www.scopus.com/inward/record.url?scp=84873491442&partnerID=8YFLogxK
U2 - 10.1109/EAIT.2012.6407873
DO - 10.1109/EAIT.2012.6407873
M3 - Conference contribution
AN - SCOPUS:84873491442
SN - 9781467318259
T3 - Proceedings - 2012 3rd International Conference on Emerging Applications of Information Technology, EAIT 2012
SP - 106
EP - 109
BT - Proceedings - 2012 3rd International Conference on Emerging Applications of Information Technology, EAIT 2012
T2 - 2012 3rd International Conference on Emerging Applications of Information Technology, EAIT 2012
Y2 - 30 November 2012 through 1 December 2012
ER -