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New Developments in Psychometrics
Independent component analysis (ICA) was developed in the signal processing and neural computation communities. Its original purpose was to solve what is called the blind source separation problem: when linear mixtures of some original source signals are observed, the goal is to recover the source signals, using minimum assumptions on the mixing matrix (i.e. blindly). This leads to a linear model that is very similar to the one used in factor analysis. What makes ICA fundamentally differentdoi:10.1007/978-4-431-66996-8_75 fatcat:6mpb4fhdavebvoiwgbbx4bhsku