Determining number of independent sources in undercomplete mixture

Naik, G and Kumar, D 2009, 'Determining number of independent sources in undercomplete mixture', Eurasip Journal on Advances in Signal Processing, vol. 2009, no. Article ID: 694850, pp. 1-5.


Document type: Journal Article
Collection: Journal Articles

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Title Determining number of independent sources in undercomplete mixture
Author(s) Naik, G
Kumar, D
Year 2009
Journal name Eurasip Journal on Advances in Signal Processing
Volume number 2009
Issue number Article ID: 694850
Start page 1
End page 5
Total pages 5
Publisher Hindawi Publishing Corporation
Abstract Separation of independent sources using independent component analysis (ICA) requires prior knowledge of the number of independent sources. Performing ICA when the number of recordings is greater than the number of sources can give erroneous results. To improve the quality of separation, the most suitable recordings have to be identified before performing ICA. Techniques employed to estimate suitable recordings require estimation of number of independent sources or require repeated iterations. However there is no objective measure of the number of independent sources in a given mixture. Here, a technique has been developed to determine the number of independent sources in a given mixture. This paper demonstrates that normalised determinant of the global matrix is a measure of the number of independent sources, N, in a mixture of M recordings. It has also been shown that performing ICA on N randomly selected recordings out of M recordings gives good quality of separation.
Subject Signal Processing
DOI - identifier 10.1155/2009/694850
Copyright notice © 2009 G. R. Naik and D. K. Kumar
ISSN 1687-6172
Additional Notes Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
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