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In this section, we will assess the performance of the proposed detector in terms of PU signal detection using the binary hypothesis test expressed in (3.10) and (3.11) for the DED-AIC and the DED-MDL detectors, respectively.
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Consequently, one has the following result: Result 2: Upon to a translation factor, the asymptotic MSRL based on the hypothesis test approach (i.e., using the binary one-sided hypothesis test given in (8)) is equivalent to the proposed MSRL based on the CRB approach (i.e., using the extension of the Smith criterion).
Biomarkers were transformed using the binary logarithm.
The binary hypothesis is used to test the algorithm as follows.
Then, the binary hypothesis test can be conducted using the generalized likelihood ratio test (GLRT) [17].
The threshold selection is crucial in the binary hypothesis test.
For a local sensor i, the binary hypothesis testing problem is denoted as follows: Fig. 1 A sensor deployment example.
This statistic is threshold dependent and uses the binary distributions.
We use the binary variables in Table 1.
The leaf images were further processed into binary images using the Make Binary command.
(hat {E}) is the output of the energy detector which is used as input for a binary hypothesis test of the CR-based HAN device.
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