Using Black Hole Algorithm to Improve EEG-Based Emotion Recognition

Table 1

Parameter setting to the entropy and the black hole algorithm.

Section	Component	Description	Value
Data selection	Number of sessions	Emotion elicitation trials	563
	Frequency	Each second has 128 samples or values	128 Hz
	Frame	To classify each frame it lasts 9 seconds, without overlapping	9 sec.
Sample entropy		Number of samples	128 samples
		Embedded dimension	2
		Probability of similarity on two simultaneous datasets	0.15
Empirical Mode Decomposition	Order	Number of IMFs	4
Black Hole Algorithm		Number of stars (solutions)	30
		Maximum iterations	100
Miscellaneous	–	Runs of the approximate approach	30
	–	Number of used cores (processors)	8