Uncertainties in signal recovery from heterogeneous and convoluted time series with principal component analysis
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Principal component analysis (PCA) is one of the most used tools for extracting low-dimensional representations of data, in particular for time series. Performances are known to strongly depend on the quality (amount of noise) and the quantity of data. We here... ...
