Independent component analysis P6
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Principal Component Analysis and Whitening Principal component analysis (PCA) and the closely related Karhunen-Lo` ve transe form, or the Hotelling transform, are classic techniques in statistical data analysis, feature extraction, and data compression, stemming from the early work of Pearson [364]. Given a set of multivariate measurements, the purpose is to find a smaller set of variables with less redundancy, that would give as good a representation as possible. This goal is related to the goal of independent component analysis (ICA). However, in PCA the redundancy is measured by correlations between data elements, while in ICA the much richer concept of...
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