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The best way to future-proof your show, of course, is to set out the parameters from the off.
In our calculation we adopt the parameters from Ref. [17].
Substituting the parameters from Theorem 1 with L=1.
The volume is transformed only if the parameters from the second pass indicate a better match than the parameters from first pass.
The simulated impedance plot using the parameters from [49] is given in Fig. 7.
Substituting the parameters from Theorem 1. Expanding the summation and using (19).
The deconvolutional layers no longer rely on the parameters from the trained ConvNet.
A second scenario used the parameters from the original dataset, thus different covariances in each group.
The design spectrum was constructed using the parameters from ASCE 7-05 (2006).
We proceed by expanding perturbatively in the parameters from Table 1 the square root of (21).
And a regression-based method is proposed to estimate the parameters from the noisy observations.
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