Independent Component Analysis (ICA): An Explanation

Independent Component Analysis (ICA) is a powerful signal-processing technique used to separate complex signals into statistically independent components. It is commonly applied to EEG (electroencephalography) and MEG (magnetoencephalography) data to identify distinct neural sources responsible for measured brain activity. ICA is particularly useful when dealing with mixed signals, where the recorded data combines various underlying …

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