Denoising Time Series Data Using Asymmetric Generative Adversarial Networks
PAKDD, pp. 285-296, 2018.
Denoising data is a preprocessing step for several time series mining algorithms. This step is especially important if the noise in data originates from diverse sources. Consequently, it is commonly used in biomedical applications that use Electroencephalography (EEG) data. In EEG data noise can occur due to ocular, muscular and cardiac a...More
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