Introduction - If you have any usage issues, please Google them yourself
Independent component analysis
(ICA) is a recently developed method in which the goal is to find a linear representation of nongaussian data so
that the components are statistically independent, or as independent as possible. Such a representation seems to
capture the essential structure of the data in many applications, including feature extraction and signal separation.
In this paper, we present the basic theory and applications of ICA, and our recent work on the subject