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Jiarui Xia and Yongshou Dai
Ground roll noise suppression is a crucial step in processing deep pre-stack seismic data. Recently, supervised deep learning methods have gained popularity in this field due to their ability to adaptively learn and extract powerful features. However, th...
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Tobias Zeulner, Gerhard Johann Hagerer, Moritz Müller, Ignacio Vazquez and Peter A. Gloor
Current methods for assessing individual well-being in team collaboration at the workplace often rely on manually collected surveys. This limits continuous real-world data collection and proactive measures to improve team member workplace satisfaction. W...
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Cheng-Jian Lin, Chun-Hui Lin and Frank Lin
The spindle of a machine tool plays a key role in machining because the wear of a spindle might result in inaccurate production and decreased productivity. To understand the condition of a machine tool, a vector-based convolutional fuzzy neural network (...
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Yuxing Li, Yilan Lou, Lili Liang and Shuai Zhang
In recent years, fuzzy dispersion entropy (FDE) has been proposed and used in the feature extraction of various types of signals. However, FDE can only analyze a signal from a single time scale during practical application and ignores some important info...
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Andres Gallego and Francisco Roman
Complex natural resonances (CNRs) extraction methods such as matrix pencil method (MPM), Cauchy, vector-fitting Cauchy method (VCM), or Prony?s method decompose a signal in terms of frequency components and damping factors based on Baum?s singularity exp...
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