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Some numerical tests are given to demonstrate the conservativeness and the performances of our method.
In Figure 8, a comparison of the detection performances of our method in the case of AWGN channel is depicted.
Due to the direct relationship between this experiment and consecutive ones problem, we also expected good performances of our method.
In this section we will also compare the performances of our method to a conventional one, such as, that one proposed by Vanderkooy and Lipshitz [4].
We evaluate the performances of our method when the QAM or PAM modulation of order 8 (8-QAM and 8-PAM) is used to transmit the symbols coded by LDPC (n=16,k=8) over GF 8).
The performances of our method have been extensively tested on the UCI machine learning repository, as well as a real clinical problem, i.e., tissue classification in prostate ultrasound images.
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Cross-validation was performed to evaluate the performance of our method and for parameter optimization.
We perform three sets of simulations to examine the performance of our method.
The choice of p influences the performance of our method.
Numerical studies demonstrate satisfactory performance of our method.
Table 4 Performance of our method on the EEG datasets.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com