Sentence examples for mean apparent ssq from inspiring English sources

In this case, the mean apparent ssq gains and synthetic site gains are the same for every MT observation (Fig. 22b).

For example, the mean apparent ssq gains from stations over the conductive structure (e.g., stations syn07 and syn19) tend to be slightly smaller than the synthetic site gains (Fig. 23b).

Fig. 26 Comparison of the gains derived from the Frobenius norm (triangles) with the mean apparent ssq gains (squares) from the 1D example, where the elements of the perturbation matrix (mathbf {D}) are normally distributed random numbers with an SD of 0.5.

In spite of the large site-to-site variation in the synthetic site gain of nearly one order of magnitude (two orders of magnitude in terms of the static shift in the apparent resistivity), its estimation error by the mean apparent ssq site gains is as small as only a few percent.

To meaningfully interpret these results, we calculated the mean apparent det and ssq gains, (bar{g}_i^{mathrm {det}}) and (bar{g}_i^{mathrm {ssq}}), using the geometric mean of the real part of the apparent gains over a given period range (as with Eq. 13).

Fig. 22 a Comparison of synthetic site gains (crosses) with the mean apparent det (diamonds) and ssq (squares) gains from the 1D example, where a set of distortion parameters with an SD of 0.3 was applied.

The apparent ssq gains from different stations and their mean values (Fig. 26) are calculated using Eqs.

Consequently, the apparent ssq gain (Section 6) should be a good approximation of the site gain.

However, the apparent ssq gain still agrees with the synthetic site gain within the standard error.

Thus, the apparent ssq gain is expected to be the more accurate approximation of the site gain when the data are strongly distorted.

It is shown that the apparent ssq gain still gives a good approximation of the site gain under the PIM model.