Underdetermined blind separation of an unknown number of sources based on Fourier transform and Matrix Factorization

Alshabrawy, Ossama, Ghoneim, Mohamed E., Salama, A. A. and Hassanien, Aboul Ella (2013) Underdetermined blind separation of an unknown number of sources based on Fourier transform and Matrix Factorization. In: 2013 Federated Conference on Computer Science and Information Systems.

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Official URL: https://ieeexplore.ieee.org/document/6643971

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.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: blind source separation, Fourier transforms, matrix decomposition, Armijo rule, Lin's projected gradient algorithm, source signals, rough-fuzzy clustering, additive noise, blind source separation, Matrix factorization, Fourier transform, Source separation, Clustering algorithms, Equations, Mathematical model;Estimation;Least squares approximations, Underdetermined Blind Source Separation, Rough Fuzzy clustering, Short Time Fourier transform, Lin's Projected Gradient, Armijo rule
Subjects: G400 Computer Science
G600 Software Engineering
G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: John Coen
Date Deposited: 16 Mar 2020 15:44
Last Modified: 17 Mar 2020 08:59
URI: http://nrl.northumbria.ac.uk/id/eprint/42499

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