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The method extracts the characteristics and calculates the DetC signals levels variation through DWT decomposition for identification of transients.
The DRDE method extracts the residue amplifier non-idealities by evaluating the digitized residue voltage probability density function (PDF).
This method extracts the speech bottleneck features which contain supervised class information and adjacent voice frames related information by changing the architecture of deep neural network (DNN), to improve of the performance speech recognition.
The experiment results show that the proposed method extracts the fatigue evolution stages information of rolling bearing effectively and much easier and more accuracy than the traditional feature trend analysis and other two traditional feature extraction methods.
Next, combining the CS-optimized fuzzy clustering and Apriori algorithm, the proposed method extracts the association rules between the shape characteristics and the forecasting error of the divided waves.
The spectral moment method extracts the information on the principal axis and its ratio to the minor axis automatically from the second-order moment calculations.
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Finally, the SMP-Gabor method extracted the best three logons that explained the whole data set.
When tested on unseen articles, the method extracted the eligibility criteria with a precision of 0.69 and a recall of 0.54.
The method extracts those parameters from FRFs of an entire specimen that contains only the spindle holder taper joint.
EMRlog method extracts this information from the EMR database log using C4.5 algorithm.
Most of existing signal processing methods extract the damage-related features from the time frequency joint spectrum which requires a quite amount of effort.
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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