Subband Blind Source Separation with Critically Sampled Filter Banks
نویسندگان
چکیده
Subband blind source separation methods have been recently proposed with the objective of reducing the computational complexity and improving the convergence rate of online adaptive algorithms. Oversampled subband structures, employing uniform DFT filter banks, are usually employed in order to avoid aliasing effects and keep enough samples to estimate the statistics of the subband signals. In this paper we present a critically sampled subband structure, composed of real-coefficients uniform filter banks and reduced-order adaptive subfilters, for the blind separation of convolutive mixtures. Through experimental results, we evaluate the impact of the filter banks and lengths of the adaptive filters on the source separation for different reverberation characteristics.
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