Independent Component Analysis - Chapter 14: Overview and Comparison of Basic ICA Methods

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Independent Component Analysis - Chapter 14: Overview and Comparison of Basic ICA Methods

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In the preceding chapters, we introduced several different estimation principles and algorithms for independent component analysis (ICA). In this chapter, we provide an overview of these methods. First, we show that all these estimation principles are intimately connected, and the main choices are between cumulant-based vs. negentropy/likelihood-based estimation methods, and between one-unit vs. multiunit methods. In other words, one must choose the nonlinearity and the decorrelation method.

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