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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Bibliographic Details
Published in:Circuits and Systems; Proceedings: Midwest Symposium on Circuits and Systems pp. 242 - 245
Main Authors: Hsiao-Chun Wu, Principe, J.C.
Format: Conference Proceeding
Language:English
Published: IEEE 1998
Subjects:
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 Access:Get full text
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Summary: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