Abstract
Blind identification of source signals is studied from both theoretical and algorithmic aspects. A mathematical structure is formulated from which the acceptable indeterminacy is represented by an equivalence relation. The concept of identifiability is then defined. Two identifiable cases are shown along with blind identification algorithms. The performance of FOBI (fourth-order blind identification), EFOBI (extended FOBI), and AMUSE algorithms is evaluated by some heuristic arguments and simulation results. It is shown that EFOBI outperforms the FOBI algorithm, and the AMUSE algorithm performs better than EFOBI in the case of nonwhite source signals. AMUSE is applied to a speech extraction problem and shown to have promising results. >
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