Survey on Independent Component Analysis

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Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation (2018, background): “t and interfering sources, which can be used in computational frameworks such as the maximum likelihood estimation (MLE). One notable approach in this category is independent component analysis (ICA) [32], [33], [34]: the target and interfering sources are decomposed into a set of statistically inde”
Underdetermined blind source separation using sparse representations (2001, methodology): “For M = N , several approaches to independent component analysis have been used in the literature (see for instance [ 6 ] for a recent survey) to numerically solve Eq. (1) while assuming only statistical independence of the source components stj .O f”
Imaging brain dynamics using independent component analysis (2001, background): “The same insight underlies “negentropy” approaches to ICA that maximize the distance of the pi(ui) from Gaussian, described in [13] and by Lee et al.”