Quadratic Dependence Measure for Nonlinear Blind Sources Separation

This work focuses on a quadratic dependence measure which can be used for blind source separation. After defining it, we show some links with other quadratic dependence measures used by Feuerverger and Rosenblatt. We develop a practical way for computing this measure, which leads us to a new solution for blind source separation in the case of nonlinear mixtures. It consists in first estimating the theoretical quadratic measure, then computing its relative gradient, finally minimizing it through a gradient descent method. Some examples illustrate our method in the post nonlinear mixtures.