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Feature extraction was implemented in the present work using two alternative approaches.
Function of signal analysis and fault feature extraction was implemented with virtual instrument technology based on LabVIEW.
In our previous studies, the SE feature extraction was implemented on an unprocessed dataset [26, 27, 28, 29] with motion and muscle artifacts.
The module of acoustic feature extraction was implemented based on the tool of openSMILE [47], an open-source software that can extract many low-level acoustic features and statistic functionals.
An efficient catalyst recycling concept via extraction was implemented, resulting in a very low catalyst leaching for both iridium and phosphorus (0.1%/h) and a steady state plant operation over 90 h.
In this study, a field test of LFG extraction was implemented under the condition of using high-density polyethylene (HDPE) geomembrane layer as the only intermediate cover on the landfill.
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The feature extraction is implemented in PHP.
The penetration feature extraction is implemented in the preprocessed signal.
Algorithms for ECG enhancement, ECG quality evaluation and ECG parameters extraction were implemented in the system.
This will cause a large calculation burden since feather extraction is implemented in a very high-dimensional vector space.
In our study, pre-processing and feature extraction were implemented in Matlab 8.3 [26] using a toolbox [27].
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