Comparison of maximum entropy and minimal mutual information in a nonlinear setting

In blind source separation (BSS), two di erent separation techniques are mainly used: minimal mutual information (MMI), where minimization of the mutual output information yields an independent random vector, and maximum entropy (ME), where the output entropy is maximized. However, it is yet unclear why ME should solve the separation problem, i.e. result in an independent vector. Yang and Amari have given a partial con

• Type: Journal
• Year: 2002
• Where: SIGPRO
• Authors: Fabian J. Theis, Christoph Bauer, Elmar Wolfgang Lang
• Keywords: Blind Source Separation, Independent Random Vector, Random Vectors, SIGPRO 2002