Contravariant adaptation on structured matrix spaces
Signal Processing
Blind sources separation algorithm based on adaptive givens rotations
ICNC'09 Proceedings of the 5th international conference on Natural computation
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Blind signal separation (BSS) is a recurrent problem in many multi-sensors applications where observations can be modelled as mixtures of N statistical independent source signals. We propose the estimation of the orthonormal transformation matrix Q in the case of whitened observations and a cost function based on the fourth-order moments. Q is described as combination of elementary Givens rotations and the optimization is carried out jointly for all the rotations. When sub-sets of angles are optimized separately the method reduces to the deflation approach which has been proved to be globally convergent. The joint estimation of Givens rotation matrices has a computational complexity O(7N/sup 2/) and, compared to other adaptive BSS, simulations demonstrate that it converges faster and achieves a better crosstalk attenuation.