Kernel-independent component analysis (KICA) is an extension of independent component analysis (ICA) that utilizes kernel methods to allow for the separation of non-linear components from data. While standard ICA is designed to separate independent sources in a linear fashion, KICA broadens this capability by applying kernel techniques, which can handle more complex relationships within the data.
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