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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)