An Alternative Perspective on Adaptive Independent Component Analysis Algorithms
- 1 November 1998
- journal article
- Published by MIT Press in Neural Computation
- Vol. 10 (8), 2103-2114
- https://doi.org/10.1162/089976698300016981
Abstract
This article develops an extended independent component analysis algorithm for mixtures of arbitrary subgaussian and supergaussian sources. The gaussian mixture model of Pearson is employed in deriving a closed-form generic score function for strictly subgaussian sources. This is combined with the score function for a unimodal supergaussian density to provide a computationally simple yet powerful algorithm for performing independent component analysis on arbitrary mixtures of nongaussian sources.Keywords
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