A general contrast function based blind source separation method for convolutively mixed independent sources

This paper presents a time-domain blind source separation algorithm based on the criterion of the general contrast function. The algorithm extends the efficient fixed-point algorithm for instantaneous mixing models to extract a source from convolutive mixed sources. A new decorrelation procedure is proposed to help the algorithm separate the rest of the sources one by one. This scalable feature enables us to extract only some of the source signals from their convolutive mixtures. Also, the algorithm does not suffer from the problems of frequency domain based algorithms on arbitrary scaling and permutations in different frequency components. Simulations on synthetic data and real-world recordings were used to verify the extended fixed-point algorithm. Results of the simulations show that the algorithm is capable of significantly suppressing the crosstalk of the extracted source signals.