A Framework on Performance Analysis of Mathematical Model-Based Classifiers in Detection of Epileptic Seizure from EEG Signals with Efficient Feature Selection

Table 4

Features extracted from DWT coefficients with PSO feature selection method.

Statistical parameters	Haar wavelet		dB4 wavelet		Sym 8 wavelet
	A	E	A	E	A	E
Mean	0.100211	39.86297	0.100678	42.9912	0.099508	42.03022
Variance	0.001501	1248.341	0.001165	2041.859	0.001941	2132.655
Skewness	−0.03815	0.753713	−0.80264	0.66277	−1.19694	0.719259
Kurtosis	12.93212	−0.94194	17.05044	−1.2422	19.47415	−1.1595
Pearson correlation coefficient	−0.01129	−0.00714	-0.00704	0.018943	0.021754	0.008678
CCA	0.13711		0.17107		0.16946