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In an underdetermined mixture system with $n$ unknown sources, it is a challenging task to separate these sources from their $m$ observed mixture signals, where $m<n$ . By exploiting the technique of sparse coding, we propose an effective approach to discover some 1-D subspaces from the set consisting of all the time-frequency (TF) representation vectors of observed mixture signals. We show...
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