Determining number of independent sources in undercomplete mixture

Publisher:
SpringerOpen
Publication Type:
Journal Article
Citation:
Eurasip Journal on Advances in Signal Processing, 2009, 2009 (NA), pp. 0 - 0
Issue Date:
2009-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2012007329OK.pdf520.94 kB
Adobe PDF
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. © 2009 G. R. Naik and D. K. Kumar.
Please use this identifier to cite or link to this item: