Abstract
Algorithms for the blind separation of sources can be derived from several different principles. This article shows that the infomax (information-maximization) principle is equivalent to the maximum likelihood. The application of the infomax principle to source separation consists of maximizing an output entropy.
Keywords
InfomaxBlind signal separationEntropy maximizationPrinciple of maximum entropySource separationEntropy (arrow of time)Maximum likelihoodMaximizationComputer scienceMathematicsIndependent component analysisMaximum likelihood sequence estimationExpectation–maximization algorithmSeparation (statistics)Artificial intelligencePattern recognition (psychology)Speech recognitionStatisticsMathematical optimization
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Publication Info
- Year
- 1997
- Type
- article
- Volume
- 4
- Issue
- 4
- Pages
- 112-114
- Citations
- 675
- Access
- Closed
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Cite This
J.-F. Cardoso
(1997).
Infomax and maximum likelihood for blind source separation.
IEEE Signal Processing Letters
, 4
(4)
, 112-114.
https://doi.org/10.1109/97.566704
Identifiers
- DOI
- 10.1109/97.566704