Fast algorithms for mutual information based independent component analysis

This paper provides fast algorithms to perform independent component analysis based on the mutual information criterion. The main ingredient is the binning technique and the use of cardinal splines, which allows the fast computation of the density estimator over a regular grid. Using a discretized f...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2004-10, Vol.52 (10), p.2690-2700
Main Author: PHAM, Dinh-Tuan
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Blind source separation
Criteria
Density
Detection, estimation, filtering, equalization, prediction
Entropy
Estimators
Exact sciences and technology
Grid computing
Independent component analysis
Information analysis
Information, signal and communications theory
Kernel
Mathematical analysis
Mutual information
On-line systems
Random variables
Signal and communications theory
Signal, noise
Source separation
Telecommunications and information theory
Vectors
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Summary:This paper provides fast algorithms to perform independent component analysis based on the mutual information criterion. The main ingredient is the binning technique and the use of cardinal splines, which allows the fast computation of the density estimator over a regular grid. Using a discretized form of the entropy, the criterion can be evaluated quickly together with its gradient, which can be expressed in terms of the score functions. Both offline and online separation algorithms have been developed. Our density, entropy, and score estimators also have their own interest.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2004.834398