Nonnegative least-correlated component analysis for separation of dependent sources by volume maximization
Although significant efforts have been made in developing nonnegative blind source separation techniques, accurate separation of positive yet dependent sources remains a challenging task. In this paper, a joint correlation function of multiple signals is proposed to reveal and confirm that the obser...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 32(2010), 5 vom: 18. Mai, Seite 875-88 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2010
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't |
| Zusammenfassung: | Although significant efforts have been made in developing nonnegative blind source separation techniques, accurate separation of positive yet dependent sources remains a challenging task. In this paper, a joint correlation function of multiple signals is proposed to reveal and confirm that the observations after nonnegative mixing would have higher joint correlation than the original unknown sources. Accordingly, a new nonnegative least-correlated component analysis (n/LCA) method is proposed to design the unmixing matrix by minimizing the joint correlation function among the estimated nonnegative sources. In addition to a closed-form solution for unmixing two mixtures of two sources, the general algorithm of n/LCA for the multisource case is developed based on an iterative volume maximization (IVM) principle and linear programming. The source identifiability and required conditions are discussed and proven. The proposed n/LCA algorithm, denoted by n/LCA-IVM, is evaluated with both simulation data and real biomedical data to demonstrate its superior performance over several existing benchmark methods |
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| Beschreibung: | Date Completed 23.06.2010 Date Revised 19.03.2010 published: Print Citation Status MEDLINE |
| ISSN: | 1939-3539 |
| DOI: | 10.1109/TPAMI.2009.72 |