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Coupling decomposition algorithm.
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The CSP decomposition can be thought of as a coupled decomposition of 2 matrices (for 2 classes) similar to a principal components analysis yielding eigenvectors and eigenvalues.
In order to overcome these drawbacks, we introduce a novel technique, the coupled-decompositions method (CDM).
This is a limiting factor in practice and in order to circumvent this drawback, we develop in this article the coupled-decompositions method.
Moreover, since the standard allocates resources in a terminal basis but each terminal may support several services, we develop a new decomposition technique, the coupled-decompositions method, that obtains the optimal service flow allocation with a small number of iterations (the improvement is significant when compared to other known solutions).
OlehSh developed the x3-x2-coupling decomposition algorithm to treat PAL spectra of studied composites.
Trapping parameters calculated within x3-x2-coupling decomposition procedure are shown to characterize adequately nanospace filling in As4S4/ZnS nanocomposites.
Positron lifetime spectra were reconstructed from unconstrained three-term decomposition procedure and further subjected to parameterization using x3-x2-coupling decomposition algorithm.
Meaningful phenomenological description of this process can be developed at the basis of semi-empirical model exploring x3-x2-coupling decomposition algorithm.
The measured lifetime spectra for uncured and light-cured composites are reconstructed from unconstrained x3-term fitting and semi-empirical model exploring x3-x2-coupling decomposition algorithm.
Positron lifetime spectra are reconstructed from unconstrained three-term decomposition and then subjected to parameterization using x3-x2-coupling decomposition algorithm.
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