The width of the error distributions converge to a non-zero value.
We find a roughly linear relation between the width of the error threshold and the fitness fluctuation strength.
For the dissolution time, the width of the error distribution for the smallest time-step parameter adopted, varies from 60 to 100 crossing times.
Given the width of the error bars, however, all that can be said with confidence is that the entropy curve for the SHR lies above that for the WKY.
Despite this decrease in the median of error, the widths of the error distributions steadily increase at 16° for all three methods, as can be clearly seen from Fig. 18 (middle).
If the three computer programs/algorithms that we applied to the images in Fig. 2 were indeed close to this ideal, we should have obtained essentially the same lattice parameter extraction results for all three of them, whereby the widths of the error bar intervals could have varied somewhat.
Reducing the widths of the error bars on the extracted lattice parameters of this example sufficiently (by, e.g., a more accurate extraction that is aided by a lower noise level) so that the approximately equal sign between the lattice vector magnitudes can be safely ruled out and/or the 60° value is excluded from the extracted lattice angle interval would be one way to deal with this ambiguity.
The parameter, C, determines the penalty assigned to the total error from misclassified samples, resulting in a trade-off between the width of the margin and the error penalty.
Thus, while in the case of acoustic noise the noise power is typically associated with the width of the noise pdf, in error concealment, the noise power can be related to the height of spikes in the noise histogram belonging to d≠0 (here: for uniform PCM quantization, natural-binary bit mapping, and BPSK modulation).
In order to determine the required number of bits in the bit-width reduced FPU, analysis of the error caused by a reduced-precision is essential.
Yang, et al. [105], analyzed the influence of zero residual voltage, coverage width of the detection unit, installation errors and deformation of detection roller, and other factors on the shape detection signal, and a relatively complete compensation model was established.
