Eigendecomposition is a technique that finds "special" vectors associated with square matrices. Eigendecomposition is the basis for many important techniques in data analysis, including principal components analyses, blind-source-separation, and other spatial filters. You'll also see a comparison between PCA and ICA. It is about 40 minutes long (sorry, a bit on the long side).
|You'll need this Matlab script as well as this ICA function (this is the original source of the jader function).|