In Section 4 we propose Neyman-Pearson test which is a most powerful test.
Our aim in this section is to establish nonrandomized Neyman-Pearson test for the hypothesis defined in the preceding section.
Neyman-Pearson test of size [alpha] for testing (59) will reject [H.sub.0], ifand only if
In order to constrain the probability of false alarm, the Neyman-Pearson test
requires that the distribution of the detection statistic under [H.sub.0] does not depend on any unknown parameters.
Section 3 introduces the background on Neyman-Pearson test and CS theory.
Neyman-Pearson Test. Statistical hypothesis testing is a crucial method to detect and classify signals.
As adopted in this paper, Neyman-Pearson test could obtain the largest [P.sub.D] under certain constrained [P.sub.F].