2020
DOI: 10.1109/jsen.2020.3007369
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WSN Sampling Optimization for Signal Reconstruction Using Spatiotemporal Autoencoder

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Cited by 15 publications
(5 citation statements)
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“…In fault diagnosis, the first step is to extract fault features from the acquired data [ 7 , 8 ]. Feature extraction is the process of obtaining fault features through signal processing [ 9 , 10 ].…”
Section: Introductionmentioning
confidence: 99%
“…In fault diagnosis, the first step is to extract fault features from the acquired data [ 7 , 8 ]. Feature extraction is the process of obtaining fault features through signal processing [ 9 , 10 ].…”
Section: Introductionmentioning
confidence: 99%
“…Some studies [26][27][28][29][30][31] also describe the fusion of different fault diagnosis technologies, which have achieved good results in certain application fields. At the same time, with regard to fault feature extraction, there have been many improved algorithms that eliminate the dependence on domain knowledge and expert experience [32,33]; and as result, great breakthroughs have been made in the automatic extraction of mechanical fault features. However, due to increasingly prominent complex nonlinear and strong interference problems, there is no immutable general model for fault diagnosis.…”
Section: Related Workmentioning
confidence: 99%
“…Specify the prefix values to identify the transmission packets with respect to proper unit specifications. 7. Estimate the transmission speed with respect to time and packet size.…”
Section: Algorithm-1: Data Rate Estimationmentioning
confidence: 99%