A Projection-Pursuit-Based Method for Blind Separation of Nonnegative Sources

This paper presents a projection pursuit (PP) based method for blind separation of nonnegative sources. First, the available observation matrix is mapped to construct a new mixing model, in which the unaccessible source matrix is normalized to be column-sum-to-one. Then, the PP method is proposed to...

Full description

Bibliographic Details
Main Authors: Yang, Z., Xiang, Y., Rong, Yue, Xie, S.
Format: Journal Article
Published: IEEE 2013
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/45510
_version_ 1848757305619775488
author Yang, Z.
Xiang, Y.
Rong, Yue
Xie, S.
author_facet Yang, Z.
Xiang, Y.
Rong, Yue
Xie, S.
author_sort Yang, Z.
building Curtin Institutional Repository
collection Online Access
description This paper presents a projection pursuit (PP) based method for blind separation of nonnegative sources. First, the available observation matrix is mapped to construct a new mixing model, in which the unaccessible source matrix is normalized to be column-sum-to-one. Then, the PP method is proposed to solve this new model, where the mixing matrix is estimated column by column through tracing the projections to the mapped observations in specified directions, which leads to the recoveryof the sources. The proposed method is much faster than Chan’s method which has similar assumptions to ours, due to the usage of the optimal projection. Also, it is more advantageous inseparating cross-correlated sources than the independence- and uncorrelation-based methods as it does not employ any statistical information of the sources. Furthermore, the new method doesnot require the mixing matrix to be nonnegative. Simulation results demonstrate the superior performance of our method.
first_indexed 2025-11-14T09:25:59Z
format Journal Article
id curtin-20.500.11937-45510
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T09:25:59Z
publishDate 2013
publisher IEEE
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-455102017-09-13T16:05:51Z A Projection-Pursuit-Based Method for Blind Separation of Nonnegative Sources Yang, Z. Xiang, Y. Rong, Yue Xie, S. Blind source separation projection pursuit linear programming nonnegative sources This paper presents a projection pursuit (PP) based method for blind separation of nonnegative sources. First, the available observation matrix is mapped to construct a new mixing model, in which the unaccessible source matrix is normalized to be column-sum-to-one. Then, the PP method is proposed to solve this new model, where the mixing matrix is estimated column by column through tracing the projections to the mapped observations in specified directions, which leads to the recoveryof the sources. The proposed method is much faster than Chan’s method which has similar assumptions to ours, due to the usage of the optimal projection. Also, it is more advantageous inseparating cross-correlated sources than the independence- and uncorrelation-based methods as it does not employ any statistical information of the sources. Furthermore, the new method doesnot require the mixing matrix to be nonnegative. Simulation results demonstrate the superior performance of our method. 2013 Journal Article http://hdl.handle.net/20.500.11937/45510 10.1109/TNNLS.2012.2224124 IEEE fulltext
spellingShingle Blind source separation
projection pursuit
linear programming
nonnegative sources
Yang, Z.
Xiang, Y.
Rong, Yue
Xie, S.
A Projection-Pursuit-Based Method for Blind Separation of Nonnegative Sources
title A Projection-Pursuit-Based Method for Blind Separation of Nonnegative Sources
title_full A Projection-Pursuit-Based Method for Blind Separation of Nonnegative Sources
title_fullStr A Projection-Pursuit-Based Method for Blind Separation of Nonnegative Sources
title_full_unstemmed A Projection-Pursuit-Based Method for Blind Separation of Nonnegative Sources
title_short A Projection-Pursuit-Based Method for Blind Separation of Nonnegative Sources
title_sort projection-pursuit-based method for blind separation of nonnegative sources
topic Blind source separation
projection pursuit
linear programming
nonnegative sources
url http://hdl.handle.net/20.500.11937/45510