Blind identification of mixtures of quasi-stationary sources using a Khatri-Rao subspace approach
Refereed conference paper presented and published in conference proceedings

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AbstractThis paper addresses the problem of blind identification of a linear instantaneous overdetermined mixture of quasi-stationary sources, using a new formulation based on Khatri-Rao (KR) subspace. A salient feature of this formulation is that it decomposes the blind identification problem into a number of per-source, structurally less complex, blind identification problems. We tackle the per-source problems by developing a specialized alternating projections (AP) algorithm. Remarkably, we prove that AP almost surely converges to a true mixing matrix column in its first iteration, assuming an ideal model condition. Simulation results show that the proposed algorithm yields competitive complexity and performance. © 2011 IEEE.
All Author(s) ListLee K.-K., Ma W.-K., Chiou Y.-L., Chan T.-H., Chi C.-Y.
Name of Conference45th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2011
Start Date of Conference06/11/2011
End Date of Conference09/11/2011
Place of ConferencePacific Grove, CA
Country/Region of ConferenceUnited States of America
Pages2169 - 2173
LanguagesEnglish-United Kingdom

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