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Blind source separation by fully nonnegative constrained iterative volume maximization

Yang, Zuyuan, Ding, Shuxue and Xie, Shengli 2010, Blind source separation by fully nonnegative constrained iterative volume maximization, IEEE signal processing letters, vol. 17, no. 9, pp. 799-802, doi: 10.1109/LSP.2010.2055854.

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Title Blind source separation by fully nonnegative constrained iterative volume maximization
Author(s) Yang, Zuyuan
Ding, Shuxue
Xie, Shengli
Journal name IEEE signal processing letters
Volume number 17
Issue number 9
Start page 799
End page 802
Total pages 4
Publisher IEEE Xplore
Place of publication Piscataway, New Jersey
Publication date 2010
ISSN 1070-9908
1558-2361
Summary Blind source separation (BSS) has been widely discussed in many real applications. Recently, under the assumption that both of the sources and the mixing matrix are nonnegative, Wang develop an amazing BSS method by using volume maximization. However, the algorithm that they have proposed can guarantee the nonnegativities of the sources only, but cannot obtain a nonnegative mixing matrix necessarily. In this letter, by introducing additional constraints, a method for fully nonnegative constrained iterative volume maximization (FNCIVM) is proposed. The result is with more interpretation, while the algorithm is based on solving a single linear programming problem. Numerical experiments with synthetic signals and real-world images are performed, which show the effectiveness of the proposed method.
Language eng
DOI 10.1109/LSP.2010.2055854
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2010, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30059305

Document type: Journal Article
Collections: School of Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.