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An improved constrained ICA with reference based unmixing matrix initialization

delete2010-01-01
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PRE
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Z
Zhan-Li Sun *
L
Li Shang
DOI:10.1016/j.neucom.2009.12.016delete
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Abstract

Abstract

En 中文
The constrained independent component analysis (cICA) provides a general framework to incorporate the prior information. To overcome the unstable problem encountered in the cICA algorithm of [2]. an improved method is proposed in this letter by using the reference based unmixing matrix initialization. Compared to the original algorithm, the prior information of references is not only used in the contrast function, but also used in the initialization. The utility of the proposed method is demonstrated by the experimental results on the artificial data and the sound signals. (C) 2010 Elsevier B.V. All rights reserved.
Keywords:
Independent component analysis
Negentropy
Blind source separation
Constrained optimization
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Journal

Neurocomputing cover
Neurocomputing
IF:
6.5
Papers:
2.5W
Citations:
6.5W

Organization

S
Suzhou Vocational University
Scholars:
138
Papers: 130
Citations: 66
C
chinese academy of sciences
Scholars:
56.3W
Papers: 44.9W
Citations: 704