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 independent component analysis.
The source code and files included in this project are listed in the project files section, please make sure whether the listed source code meet your needs there.
Blind source separation based on multi user kurtosis in matlab
Brain message v 1.0 to write secret messages into fmri in matlab
Circuit analysis toolbox in matlab
Repeated measures single-factor analysis of variance test. in matlab
Three-way analysis of variance with repeated measures on three factors test. in matlab
Three-way analysis of variance with repeated measures on one factor test. in matlab
Data processing module for ion acceleration experiment in matlab
Circular statistics toolbox (directional statistics) in matlab
Grtheory graph theory toolbox in matlab
Digital image correlation and tracking in matlab
Peak fitter in matlab