Source separation in systems with correlated sources using NMF

Non-negative Matrix Factorization (NMF) has been used for source separation in various fields. However, the existing methods have ignored the presence of interactions among sources/measurements which leads to incorrect results. Interactions are common in a multivariate process where the variables ar...

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Bibliographic Details
Published in:Digital signal processing 2010-03, Vol.20 (2), p.417-432
Main Authors: Babji, S., Tangirala, A.K.
Format: Article
Language:English
Subjects:
Algorithms
Computer simulation
Correlation
Digital signal processing
Factorization
Interaction
Multivariate spectra
Non-negative matrix factorization
Separation
Signatures
Source identification
Utilities
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Summary:Non-negative Matrix Factorization (NMF) has been used for source separation in various fields. However, the existing methods have ignored the presence of interactions among sources/measurements which leads to incorrect results. Interactions are common in a multivariate process where the variables are physically related/correlated with one another (for example: pressure–temperature dependency in an industrial process). In this work, conventional methods are extended to take into account the interactions. The contributions of this work are as follows: (i) an augmented NMF method to correctly determine the number of sources in the presence of multiple interactions; (ii) an algorithm to identify the correct signatures of the physical sources. The conventional method of NMF is shown to be a special case of the proposed method. Simulation studies are presented to demonstrate the practicality and utility of the proposed method.
ISSN:1051-2004
1095-4333
DOI:10.1016/j.dsp.2009.06.021