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In the model, the data variables are assumed to be linear mixtures of some unknown latent variables, and the mixing system is also unknown.
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A BOLD signal can be assumed to be a linear mixture of the sources influencing BOLD intensity level.
Concerning the EEG, it is assumed that the recorded signal is a linear mixture of unknown sources within the brain.
While not always the case in practice, it is commonly assumed (as it is here) that at each pixel the spectral signature is a linear mixture of each of the endmembers present in the scene.
So, the GEW density function is a linear mixture of EEW densities.
It reveals that the GEW density function is a linear mixture of EW (when α>0) and Weibull (when α=0) densities.
Equation (10) reveals that the EMO-G density function is a linear mixture of exp-G density functions.
Value the independent components able to be attained by discovering the correct linear mixtures of the observational variables, since mixing can be inverted as (5) U = S = A − 1 X = W X. FastICA is the most widely used method of ICA [ 55].
It is noted in Syed et al. [3] that blind source separation problems are considered tractable if they involve linear mixtures of the sources and that it is necessary to know something about the structure of the sources or something about the mixing matrix that combines them.
The classical BSS separation approach that tries to recover all the original signals starting from the linear mixtures of them can be adapted to an extraction approach that estimates only one source, since we are only interested in the clinically significant quasiperiodic atrial signal.
In [17], a Bayesian approach for blind separation of linear mixtures of sources was developed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com