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Table 3 The average number of selected features per channel after applying the hybrid feature selection algorithm.

From: Application of a hybrid wavelet feature selection method in the design of a self-paced brain interface system

Channel/Subject ID AB1 AB2 AB3 AB4
F 1 -FC 1 3.6 (1.14) 3 (1.22) 1.8 (0.84) 3 (0.71)
F 1 -F z 0 (0) 0 (0) 0 (0) 3.4 (0.55)
F 2 -F z 0 (0) 1.6 (0.89) 0.4 (0.55) 0 (0)
F 2 -FC 2 0.2 (0.45) 2 (0.71) 0.8 (0.84) 0.4 (0.55)
FC 3 -FC 1 1 (0) 1 (0) 1.6 (0.89) 0 (0)
FC 3 -C 3 1 (0.71) 3 (0) 2.4 (1.14) 1.6 (0.55)
FC 1 -FC z 0 (0) 1 (0) 0.6 (0.55) 1.2 (0.84)
FC 1 -C 1 4.6 (0.55) 2.8 (0.45) 0 (0) 1.2 (0.45)
FC z -FC 2 0 (0) 2.2 (0.45) 0.6 (0.55) 0 (0)
C 1 -C z 1.6 (0.55) 0.4 (0.55) 3.6 (1.14) 1.2 (0.45)
C 2 -C 4 0.6 (0.55) 2.2 (0.45) 4.4 (0.89) 2.6 (0.89)
FC 2 -FC 4 4.2 (0.45) 1.6 (0.89) 2.2 (1.10) 3.4 (1.14)
FC 4 -C 4 3.2 (0.45) 2 (1) 1.8 (0.84) 4.4 (0.55)
FC 2 -C 2 2 (0) 2.2 (0.45) 0.6 (0.55) 2.2 (0.45)
FC z -C z 1.6 (0.89) 0.6 (0.55) 0.2 (0.45) 0.8 (0.45)
C 3 -C 1 1 (0.71) 2 (0) 2 (0) 0 (0)
C z -C 2 3.8 (0.45) 0 (0) 0 (0) 0.6 (0.55)
F z -FC z 2.2 (1.30) 1.6 (0.55) 0.4 (0.55) 1 (0.71)