Fast Algorithms for Mutual Information Based Independent Component Analysis .

This paper provides fast algorithms to perform independent component analysis based on the mutual information criterion. The main ingredient is the binning technique and the use of cardinal splines, which allows the fast computation of the density estimator over a regular grid. Using a discretized form of the entropy, the criterion can be evaluated quickly together with its gradient, which can be expressed in terms of the score functions. Both offline and online separation algorithms have been developed. Our density, entropy, and score estimators also have their own interest.