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The essence behind independent component analysis is the assumption of statistical independence of the sources.
Factor analysis and independent component analysis.
Plenary Lecture, Independent Component Analysis 2000, Helsinki, Finland.
Lee S-I, Batzoglou S. Application of independent component analysis to microarrays.
Independent component analysis was performed to identify components representing eye movements and muscle artifacts60.
Independent component analysis identified five neural circuits.
Probabilistic independent component analysis was used to separate resting fMRI data into DMN and SMN components.
Hyvärinen, A. Fast and robust fixed-point algorithms for independent component analysis.
The default mode network and EEG alpha oscillations: an independent component analysis.
Functional networks for cognitive control in a stop signal task: independent component analysis.
Jung, T. P. et al. Imaging brain dynamics using independent component analysis.
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