Performing Nonlinear Blind Source Separation With Signal Invariants
نویسندگان
چکیده
منابع مشابه
Blind Source Separation for Signal Processing Applications
Blind Source Separation (BSS) is a statistical approach to separating individual signals from an observed mixture of a group of signals. BSS relies on only very weak assumptions on the signals and the mixing process (hence the “blind” descriptor) and this blindness enables the technique to be used in a wide variety of situations. Research in the field of Blind Source Separation has resulted in ...
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Blind source separation (BSS) and the closely related Independent Component Analysis (ICA) have recently drawn a lot of attention in unsupervised neural learning and statistical signal processing 1, 2, 3]. In the basic linear case, ICA and BSS use the same data model x(t) = As(t) = m X i=1 s i (t)a i : (1) Here x(t) is the n-dimensional t:th data vector, s 1 (t); : : : ; s m (t) are the respect...
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ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2010
ISSN: 1053-587X,1941-0476
DOI: 10.1109/tsp.2009.2034916