Blind Source Separation Algorithms with Matrix Constraints
نویسنده
چکیده
In many applications of Independent Component Analysis (ICA) and Blind Source Separation (BSS) estimated sources signals and the mixing or separating matrices have some special structure or some constraints are imposed for the matrices such as symmetries, orthogonality, non-negativity, sparseness and specified invariant norm of the separating matrix. In this paper we present several algorithms and overview some known transformations which allows us to preserve several important constraints. Computer simulation experiments confirmed validity and usefulness of the developed algorithms. key words: Blind sources separation, independent component analysis with constraints, non-negative blind source separation
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تاریخ انتشار 2003