Independent Component Analysis (ICA) is a computational technique used to separate a multivariate signal into additive, independent components. It is often applied in various fields, including signal processing and data analysis, where it helps to extract meaningful signals from mixed data by leveraging statistical independence. This method is particularly useful in scenarios involving real-time structural health monitoring, where it aids in identifying distinct patterns from complex data sets collected from sensors.
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