Bayesian Statistics
Independent Component Analysis (ICA) is a computational method used to separate a multivariate signal into additive, independent components. This technique is particularly useful when dealing with mixed signals, allowing for the identification and extraction of underlying factors that are statistically independent from one another. ICA is widely applied in fields like neuroscience for brain signal processing and in image processing to enhance features by isolating independent sources.
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