DocumentCode :
3318596
Title :
Estimation of Source Signals Number and Underdetermined Blind Separation Based on Sparse Representation
Author :
Tan, Beihai ; Li, Xiaolu
Author_Institution :
Coll. of Electron. & Commun. Eng., South China Univ. of Technol., Guangzhou
Volume :
2
fYear :
2006
fDate :
3-6 Nov. 2006
Firstpage :
1730
Lastpage :
1733
Abstract :
In underdetermined blind separation, the number of sensors is less than that of source signals, and it is well known that source signals can be recovered through the two-step algorithms generally. But people often suppose that the number of source signals is known when they estimate the mixture matrix by the k-mean clustering algorithm. In fact, the number of source signals is unknown or blind, so it is very important to estimate the number of source signals first. In this paper, a new two-step algorithm is proposed, which not only can estimate the number of source signals but also get the mixture matrix instead of k-mean algorithm
Keywords :
blind source separation; pattern clustering; signal representation; sparse matrices; blind separation; k-mean clustering; mixture matrix; source signal number estimation; sparse representation; two-step algorithm; Algorithm design and analysis; Clustering algorithms; Educational institutions; Equations; Image restoration; Linear programming; Signal processing; Signal processing algorithms; Signal restoration; Sparse matrices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security, 2006 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
1-4244-0605-6
Electronic_ISBN :
1-4244-0605-6
Type :
conf
DOI :
10.1109/ICCIAS.2006.295356
Filename :
4076262
Link To Document :
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