As shown later in Figure 13, all the three treatments (Gaussian approximation, mean- approximation, and PSAM) result in very similar decoding performance.
For simulating various edge designs, we use the tight-binding approximation, mean-field scheme for the Hubbard model and the Landauer-Büttiker formalism.
In the case of Gaussian mixture approximation, mean values μ1, μ2 and the weights a1,a2 can be estimated from the sample set of m s → v ( k ) [25].
Janssens et al. [ 4] used the approximation of c n = c1, but in preliminary studies we recognized that this approximation meant that the equality of E(g x ) with the input (and key benchmark) parameter K was lost.
The adjustment factor used in the present study was an approximation meant to account for the general pattern of insulin fills and provides an estimated days' supply that the authors believe is more accurate than the days' supply directly from pharmacy claims.
When continuous values were described by median and IQR or range instead of mean and SD, the following formula was used for approximations: Mean = Median; SD = IQR/1.35; if 15 < n <70, SD = (b a)/4, (Minimum (a), Maximum (b)); if n >70, SD = (b a)/6 [ 27, 28].
For the models derived as approximations, this means that the final approximation, though preceding steps in the derivation, should also be given in order to document the process.
Further, we discuss the degree of approximation by means of the weighted spaces.
