Table 2: This table contains the results from verification simulation, which used the input parameters (3,3,0.5). The first column lists the detectors. The second column lists the probabilities of detection from Table 1 for the same input parameters. The third column liststhe probability of detection based on 10⁶ iterations with a FAP of 1%, while the accompanying errors are the standard deviation calculates from the 100 subsets of 10⁴ iterations in the total sample. The last two columns show the probabilities of detection with false alarm probabilities of 10^-3 and 10^-4 respectively.
Probabilities False Alarm Probability

Detector from Table 1 $10^{-2} \pm {\rm err}$ 10^-3 10^-4

BLS 0.1393 $0.1478 \pm 0.0069$ 0.0519 0.0155

Bayesian 0.0500 $0.0505 \pm 0.0034$ 0.0091 0.0016

Correlation 0.3920 $0.3842 \pm 0.0128$ 0.1786 0.0670

Matched filter 0.4590 $0.4517 \pm 0.0123$ 0.2313 0.0943

Deeg's 0.3617 $0.3804 \pm 0.0114$ 0.1783 0.0713

**Table 2:** This table contains the results from verification simulation, which used the input parameters (3,3,0.5). The first column lists the detectors. The second column lists the probabilities of detection from Table 1 for the same input parameters. The third column liststhe probability of detection based on 10⁶ iterations with a FAP of 1%, while the accompanying errors are the standard deviation calculates from the 100 subsets of 10⁴ iterations in the total sample. The last two columns show the probabilities of detection with false alarm probabilities of 10^-3 and 10^-4 respectively.
	Probabilities	False Alarm Probability
Detector	from Table 1	$10^{-2} \pm {\rm err}$	10^-3	10^-4
BLS	0.1393	$0.1478 \pm 0.0069$	0.0519	0.0155
Bayesian	0.0500	$0.0505 \pm 0.0034$	0.0091	0.0016
Correlation	0.3920	$0.3842 \pm 0.0128$	0.1786	0.0670
Matched filter	0.4590	$0.4517 \pm 0.0123$	0.2313	0.0943
Deeg's	0.3617	$0.3804 \pm 0.0114$	0.1783	0.0713

Source LaTeX | All tables | In the text