Underdetermined Blind Separation using modified subspace-based algorithm in the time-frequency domain

To solve the underdetermined blind separation (UBSS) problem, Aissa-El-Bey et al. have proposed the significant subspace-based algorithms in the time-frequency (TF) domain, where a fixed ( maximum) value of K, i.e., the number of active sources overlapping at any TF point, is considered for simplicity. In this paper, based on the principle component analysis (PCA) technology, we propose a modified algorithm by estimating the number K for selected frequency bins where most energy is concentrated. Improved performances are obtained without increasing complexity.