INDEPENDENT COMPONENT ANALYSIS THROUGH DIRECT ESTIMATION OF THE MUTUAL INFORMATION
Georges A. Darbellay 1 and Petr Tichavsky 2, 2 Institute of Information Theory and Automation, Academy of Sciences
e-mail: georges.darbellay@epfl.ch, e-mail: tichavsk@utia.cas.cz
We introduce an algorithm for the estimation of the mu-
tual information between several signals. This algorithm
also provides a convenient way of estimating the entropy of
scalar signals. The algorithm uses a data-dependent par-
titioning of the observation space and has a relatively low
computational cost. Matlab code is available. The useful-
ness of this approach in solving the independent component
analysis problem is demonstrated on the separation of a lin-
ear mixture of two and three real-world speech data sets.