Table 2. Optimal parameters for the different detector types for the different SNRs and signal model. These parameters were identified using procedure described in Algorithm 1 on the 50 trials from the training datasets.

Detector type	Parameters	SNR 0dB			SNR -3dB
		Gaussian	Laplacian	Biophysical	Gaussian	Laplacian	Biophysical
Modified Hodges	Weight	1	1	1	1	1	1
	LPF cut-off (Hz)	7.5	7.5	4.5	6.5	5.5	4.5
AGLR-G	Window size (s)	0.1	0.1	0.15	0.1	0.15	0.15
	Weight	2	1	3	1	1	1
AGLR-L	Window size (s)	0.1	0.1	0.1	0.1	0.15	0.2
	Weight	2	1	1	1	1	1
Fuzzy Entropy	Window size (ms)	60	80	100	90	70	100
	Weight	1	1	2	1	1	1
Modified Lidierth	LPF cut-off	9.5	9.5	9.5	9.5	9.5	7.5
	Weight	1	1	1	1	1	1
	m	20	25	5	25	55	25
	T1	30	30	30	30	60	30
Hodges	Window size (s)	0.1	0.1	0.1	0.1	0.1	0.1
	Weight	1	1	1	1	1	1
	LPF cut-off (Hz)	9.5	9.5	9.5	9.5	8.5	9.5
RMS	Window size (s)	0.12	0.12	0.12	0.12	0.12	0.12
	Weight	1	1	1	1	1	1
	Window shift (ms)	40	40	40	40	40	40
	Time threshold (ms)	40	40	40	40	40	40
Lidierth	Window size (s)	0.1	0.1	0.1	0.1	0.1	0.1
	Weight	1	1	1	1	1	1
	m	10	10	5	20	25	25
	T1	30	30	30	30	30	30
TKEO	HPF cut-off (Hz)	5	5	5	15	20	15
	Window size (s)	0.1	0.1	0.1	0.1	0.1	0.1
	Weight	1	1	1	1	1	1
	T1	30	30	30	30	30	30
Bonato	Weight	1	2	2	2	1	2
	m	10	25	20	20	20	25
	T1	30	30	30	30	60	30
Sample Entropy	Window size (ms)	50	50	50	50	50	50
	Weight	1	1	1	1	1	1
	Tolerance for distance	0.5	1.5	0.5	0.5	1.5	0.5
CWT	Weight	1.1	1.2	1	1.1	1	1.4
SSA	Window size (ms)	52	50	50	50	50	50