2010年9月
Blind Source Separation by Fully Nonnegative Constrained Iterative Volume Maximization
IEEE SIGNAL PROCESSING LETTERS
- ,
- ,
- 巻
- 17
- 号
- 9
- 開始ページ
- 799
- 終了ページ
- 802
- 記述言語
- 英語
- 掲載種別
- DOI
- 10.1109/LSP.2010.2055854
- 出版者・発行元
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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 et al. 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.
- リンク情報
- ID情報
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- DOI : 10.1109/LSP.2010.2055854
- ISSN : 1070-9908
- Web of Science ID : WOS:000282307800001