Yue-hong Shen

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—This paper addresses the problem of blind source separation (BSS) of n independent sources from their m linear mixtures in the over-determined cases (m n >) with unknown and dynamically changing number of sources. The system architecture including an on-line source number estimator and an auto-adjust separation mechanism is considered based on the(More)
Conventional linear instantaneous mixing model becomes unsuitable if propagation time delays are taken into account. A blind separation algorithm based on second-order Taylor approximation for delayed sources (SOTADS) is presented, under the constraint that time delays are small in comparison with the coherence time of each source. Simulation results(More)
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(More)
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