Blind separation of underdetermined mixtures with additive white and pink noises

Alshabrawy, Ossama, Hassanien, Aboul ella, Awad, W. A. and Salama, A. A. (2014) Blind separation of underdetermined mixtures with additive white and pink noises. In: 13th International Conference on Hybrid Intelligent Systems, HIS 2013, 4-6th Oct 2013, Gammarth, Tunisia.

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Abstract

This paper presents an approach for underdetermined
blind source separation in the case of additive Gaussian
white noise and pink noise. Likewise, the proposed approach is applicable in the case of separating I + 3 sources from I mixtures with additive two kinds of noises. This situation is more challenging and suitable to practical real world problems. Moreover, unlike to some conventional approaches, the sparsity conditions are not imposed. Firstly, the mixing matrix is estimated based on an algorithm that combines short time Fourier transform and rough-fuzzy clustering. Then, the mixed
signals are normalized and the source signals are recovered using modified Gradient descent Local Hierarchical Alternating Least Squares Algorithm exploiting the mixing matrix obtained from the previous step as an input and initialized by multiplicative algorithm for matrix factorization based on alpha divergence. The experiments and 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 some conventional approaches.

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