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The throughput and residual BER performances of pattern 1 are opposite to those of pattern 2 because of the parameter settings shown in Table 1.
The throughput and residual BER performances of pattern 1 are also opposite to those of pattern 2 because of the parameter settings shown in Table 2 like the AWGN case.
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This is the first study that systematically characterizes interactions between analysis model and signal parameters (such as magnitude, variance and correlation) on the performance of pattern classifiers for fMRI.
We experimentally show that the spike-time data produced by the temporal encoding techniques achieve comparable (superior in some cases) performance of pattern recognition in comparison to the use of the whole raw data.
The objective of this article was to improve the performance of pattern recognition systems when there is an overlapping feature vectors due to non-stationarity of the signals or the commonality that exist among different classes.
Since higher dimensional feature vectors contain several irrelevant features that reduce the performance of pattern recognition methods, feature selection by itself can be used in most of the modern data classification methods to combat the issues resulting from the curse of high dimensionality [18, 19].
Previous studies have assessed the performance of pattern decoders in estimating sound location from the responses of ensembles of cortical neurons.
The performance of Patterns by Deidre Cooper and Tilbury is wonderfully dedicated, while Piano, Violin, Viola, Cello seems just as compelling on disc as it was live in Huddersfield.
The performance benefits of pattern deviation score - based input data have been shown [ 21].
Therefore, these data were discarded and we will thus only report the data of the performances of the patterns.
Figure 2B also shows the performance of the pattern matching decoder.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com