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SIGPRO
2002

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

13 years 10 months ago
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
Fabian J. Theis, Christoph Bauer, Elmar Wolfgang L
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where SIGPRO
Authors Fabian J. Theis, Christoph Bauer, Elmar Wolfgang Lang
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