Volume 4 Number 7 (Jul. 2009)
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JCP 2009 Vol.4(7): 681-688 ISSN: 1796-203X
doi: 10.4304/jcp.4.7.681-688

Multiresolution Subband Blind Source Separation: Models and Methods

Hongwei Li1, Rui Li2, Fasong Wang1
1School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, P.R.China
2School of Sciences, Henan University of Technology, Zhengzhou 450052, P.R.China


Abstract—The goal of this paper is to review the multiresolution subband Blind Source Separation (MRSBSS) methods, classify them into different categories, and identify new trends. After the perspective of MRSBSS is briefly presented, the general and detailed definition of the MSBSS model is given, the relationships among BSS, Independent Component Analysis (ICA) and MRSBSS method are discussed simultaneously. Then, the state-of-theart MRSBSS algorithms: adaptive filter based method and sparsity based multiscale ICA method are constructed and overviewed in detail from different theory base. The paper concludes by discussing the impact of multiresolution subband on BSS research and outlining potential future research directions and applications.

Index Terms—Independent Component Analysis(ICA), Blind Source Separation(BSS), Independent Subspace Analysis(ISA), Subband; Multiresolution, Wavelet; Wavelet Packets.

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Cite: Hongwei Li, Rui Li, Fasong Wang, "Multiresolution Subband Blind Source Separation: Models and Methods," Journal of Computers vol. 4, no. 7, pp. 681-688, 2009.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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