Independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents. This is done by assuming that the subcomponents are non-Gaussian signals and that they are statistically independent from each other. ICA is a special case of blind source separation. A common example application is the "cocktail party problem" of listening in on one person's speech in a noisy room.
The following Matlab project contains the source code and Matlab examples used for blind source separation based on multi user kurtosis.
This file implements the Multi User Kurtosis Algorithm for Blind Source Separation (see  for more details about the method).
The following Matlab project contains the source code and Matlab examples used for pca and ica package.
This package contains functions that implement Principal Component Analysis (PCA) and its lesser known cousin, Independent Component Analysis (ICA).