DocumentCode
771606
Title
Mutual information approach to blind separation of stationary sources
Author
Pham, Dinh Tuan
Author_Institution
Lab. of Modeling & Comput., CNRS, Grenoble, France
Volume
48
Issue
7
fYear
2002
fDate
7/1/2002 12:00:00 AM
Firstpage
1935
Lastpage
1946
Abstract
This paper presents a unified approach to the problem of blind separation of sources, based on the concept of mutual information. This concept is applied to the whole source sequences as stationary processes and thus provides a universal contrast applicable to both the instantaneous and convolutive mixture cases. For practical implementation, we introduce several degraded forms of this contrast, computable from a finite-dimensional distribution of the reconstructed source processes only. From them, we derive several sets of estimating equations, generalizing those considered earlier
Keywords
Gaussian processes; Markov processes; convolution; entropy; signal reconstruction; Gaussian processes; Markovian processes; blind separation; convolutive mixture; entropy; estimating equations; finite-dimensional distribution; instantaneous mixture; mutual information; reconstructed source processes; source sequences; stationary processes; stationary sources; Computational modeling; Convolution; Degradation; Distributed computing; Entropy; Equations; Image reconstruction; Independent component analysis; Mutual information; Proposals;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.2002.1013134
Filename
1013134
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