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

Theis, Fabian J. and Bauer, Christoph and Lang, Elmar (2002) Comparison of maximum entropy and minimal mutual information in a nonlinear setting. Signal Processing 82, pp. 971-980.

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Other URL: http://homepages.uni-regensburg.de/~thf11669/publications/theis01memmi_SP.pdf


In blind source separation (BSS), two different 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, ie. result in an independent vector. Yang and Amari ...


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Item type:Article
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Projects:Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht
Dewey Decimal Classification:500 Science > 530 Physics
500 Science > 570 Life sciences
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Deposited on:20 Mar 2007
Last modified:04 Oct 2010 09:25
Item ID:1552
Owner only: item control page
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