Minimum entropy algorithms for source separation

The minimum entropy or maximum likelihood estimation can be utilized in blind source separation problem. Based on the local generalized Gaussian probability density model, a set of general anti-Hebbian rules can be derived. This set of adaptation rules give promising results when we test the real re...

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Veröffentlicht in:Circuits and Systems; Proceedings: Midwest Symposium on Circuits and Systems S. 242 - 245
Hauptverfasser: Hsiao-Chun Wu, Principe, J.C.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 1998
Schlagworte:
Blind source separation
Entropy
Equations
Finite impulse response filter
Gaussian distribution
Maximum likelihood estimation
Noise reduction
Probability density function
Source separation
Testing
ISBN:9780818689147, 0818689145
Online-Zugang:Volltext
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Zusammenfassung:The minimum entropy or maximum likelihood estimation can be utilized in blind source separation problem. Based on the local generalized Gaussian probability density model, a set of general anti-Hebbian rules can be derived. This set of adaptation rules give promising results when we test the real recordings.
ISBN:9780818689147
0818689145
DOI:10.1109/MWSCAS.1998.759478