A recursive least-squares extension of the natural gradient algorithm for blind signal separation of audio mixtures

M. Elsabrouty, T. Aboulnasr, M. Bouchard

Abstract


An algorithm named the Quasi-RLS Stiefel, that combines the principles of natural-gradient on different manifolds and RLS-based algorithms, was presented for blind signal separation (BSS) of audio mixtures. A mixture of audio data files sampled at 8 kHz and of duration 3.7 seconds were tested to compare the different BSS algorithms. It was observed that the new algorithm converges much faster than the other algorithms. It was found by the simulation results that the algorithm was suitable for BSS.

Keywords


Approximation theory; Audio systems; Computer simulation; Convergence of numerical methods; Matrix algebra; Maximum likelihood estimation; Natural frequencies; Parameter estimation; Probability density function; Audio mixtures; Blind signal separation (BSS); Gradient algorithms; Recrusive-Least-Squares (RLS)

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