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The dimension mismatch is generally the case faced for two coefficient matrices of adjacent orientations.
To do this, we introduce two coefficient factors for objective and subjective weights of decision makers.
Neither of the two coefficient estimates indicate, that a high or low caseload causes the welfare agency to adopt a certain sanction approach.
We obtain two coefficient functions from one expression function.
The two expression matrices have dimensions s× m and s× n, respectively, and will be factored into W and two coefficient matrices H1 and H2.
We first applied FPCA technique on two coefficient functions w0 t) and w1 t) separately; then we combined two groups of the selected functional principal component scores as aggregated features before we provided them to classifier.
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Hence, we perform sensitivity analysis to these two coefficients.
Nevertheless, neither of these two coefficients are statistically significant.
The two coefficients are related as follows: {T}_{11}=10underset{10}{ log}left 1-left|{S}_{11}right|^2right kern1em.
The two coefficients in Izbash's law are quantified.
The primal auxiliary filter is of 5 taps, whose first three coefficients are,, and is of 3 taps with the first two coefficients,.
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CEO of Professional Science Editing for Scientists @ prosciediting.com