|
|
|
|
| LEADER |
01000caa a22002652 4500 |
| 001 |
NLM19648233X |
| 003 |
DE-627 |
| 005 |
20250211093058.0 |
| 007 |
cr uuu---uuuuu |
| 008 |
231223s2010 xx |||||o 00| ||eng c |
| 024 |
7 |
|
|a 10.1109/TPAMI.2009.72
|2 doi
|
| 028 |
5 |
2 |
|a pubmed25n0655.xml
|
| 035 |
|
|
|a (DE-627)NLM19648233X
|
| 035 |
|
|
|a (NLM)20299711
|
| 040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
| 041 |
|
|
|a eng
|
| 100 |
1 |
|
|a Wang, Fa-Yu
|e verfasserin
|4 aut
|
| 245 |
1 |
0 |
|a Nonnegative least-correlated component analysis for separation of dependent sources by volume maximization
|
| 264 |
|
1 |
|c 2010
|
| 336 |
|
|
|a Text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a ƒaComputermedien
|b c
|2 rdamedia
|
| 338 |
|
|
|a ƒa Online-Ressource
|b cr
|2 rdacarrier
|
| 500 |
|
|
|a Date Completed 23.06.2010
|
| 500 |
|
|
|a Date Revised 19.03.2010
|
| 500 |
|
|
|a published: Print
|
| 500 |
|
|
|a Citation Status MEDLINE
|
| 520 |
|
|
|a 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
|
| 650 |
|
4 |
|a Journal Article
|
| 650 |
|
4 |
|a Research Support, N.I.H., Extramural
|
| 650 |
|
4 |
|a Research Support, Non-U.S. Gov't
|
| 700 |
1 |
|
|a Chi, Chong-Yung
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Chan, Tsung-Han
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Wang, Yue
|e verfasserin
|4 aut
|
| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1998
|g 32(2010), 5 vom: 18. Mai, Seite 875-88
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
|
| 773 |
1 |
8 |
|g volume:32
|g year:2010
|g number:5
|g day:18
|g month:05
|g pages:875-88
|
| 856 |
4 |
0 |
|u http://dx.doi.org/10.1109/TPAMI.2009.72
|3 Volltext
|
| 912 |
|
|
|a GBV_USEFLAG_A
|
| 912 |
|
|
|a SYSFLAG_A
|
| 912 |
|
|
|a GBV_NLM
|
| 912 |
|
|
|a GBV_ILN_350
|
| 951 |
|
|
|a AR
|
| 952 |
|
|
|d 32
|j 2010
|e 5
|b 18
|c 05
|h 875-88
|