DocumentCode :
1866093
Title :
Underdetermined blind separation of an unknown number of sources based on Fourier transform and Matrix Factorization
Author :
Alshabrawy, Ossama S. ; Ghoneim, Mohamed Elsayed ; Salama, A.A. ; Hassanien, Aboul Ella
Author_Institution :
Dept. of Math. & Comput. Sci., Damietta Univ., Damietta, Egypt
fYear :
2013
fDate :
8-11 Sept. 2013
Firstpage :
19
Lastpage :
25
Abstract :
This paper presents an approach for underdetermined blind source separation that can be applied even if the number of sources is unknown. Moreover, the proposed approach is applicable in the case of separating I+3 sources from I mixtures without additive noise. This situation is more challenging and suitable to practical real world problems. Also, the sparsity conditions are not imposed unlike to those employed by some conventional approaches. Firstly, the number of source signals are estimated followed by the estimation of the mixing matrix based on the use of short time Fourier transform and rough-fuzzy clustering. Then, source signals are normalized and recovered using modified Lin´s projected gradient algorithm with modified Armijo rule. The simulation results show that the proposed approach can separate I+3 source signals from I mixed signals, and it has superior evaluation performance compared to conventional approaches.
Keywords :
Fourier transforms; blind source separation; matrix decomposition; Armijo rule; Fourier transform; Lin´s projected gradient algorithm; Matrix factorization; additive noise; blind source separation; rough-fuzzy clustering; source signals; Clustering algorithms; Equations; Estimation; Least squares approximations; Mathematical model; Source separation; Armijo rule; Lin´s Projected Gradient; Rough Fuzzy clustering; Short Time Fourier transform; Underdetermined Blind Source Separation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on
Conference_Location :
Krako??w
Type :
conf
Filename :
6643971
Link To Document :
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