Stacked autoencoders trained in two stages reduce noise in mathematical and geophysical signals by learning a lower-dimensional representation that reconstructs the clean component.
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Stacked autoencoders based machine learning for noise reduction and signal reconstruction in geophysical data
Stacked autoencoders trained in two stages reduce noise in mathematical and geophysical signals by learning a lower-dimensional representation that reconstructs the clean component.