Title
Dark-Point Component Analysis: Nonnegative Blind Source Separation Based on Jaccard Index
Abstract
A simplicial cone can be employed in nonnegative blind source separation (N-BSS). Nevertheless, the coordinate origin may not be a dark-point, and in this case, it is challenging to implement N-BSS with a simplicial cone. We propose an algorithm for finding dark-points based on the minimum Jaccard index (MJI) criterion-dark-point component analysis (DCA). This method only needs to assume source boundedness and nonnegativity instead of local dominance, full additivity, and sparsity. On the other hand, mixing data scatter plots are usually confined as tear-drop-shaped or deltoid. However, DCA does not need such restrictions. DCA can also be applied to blind source separation (BSS) in which the sources are strictly positive, and the result is the same as that of N-BSS.
Year
DOI
Venue
2022
10.1007/s00034-022-01969-w
Circuits, Systems, and Signal Processing
Keywords
DocType
Volume
Blind Source Separation (BSS), Nonnegative BSS (N-BSS), Dark-point Component Analysis (DCA), Minimum Jaccard Index (MJI), Simplicial Cone
Journal
41
Issue
ISSN
Citations 
7
0278-081X
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Zhao, Mingzhan100.34
xie210636.98
Chang, Xinyue300.34
Zhao Wei42320.57
Zhang, Zhimin500.34