Sentence examples for model roughness and from inspiring English sources

The trade-off parameters α2 and β2 are constant factors of the model roughness and the strength of the galvanic distortion, respectively.

The inversion code seeks the model vector that minimises the objective function, which is a weighted sum of the data misfit, model roughness and strength of the galvanic distortion.

The optimal smoothing model was achieved through adjusting the normalized smoothing factor, which is usually determined by using a trade-off value between model roughness and data misfit (Fig. 5a).

This code performs smoothness-constrained 2-D inversion based on the ABIC minimization method, where trade-off parameters between data misfit, model roughness, and static shift are estimated to minimize the misfit functional, assuming that static shifts follow Gaussian distributions.

To find a suitable value of, the inversion procedure is repeated with different values of 5, 10, 15....... 50, 100 and an L curve (Hansen, 1998) is plotted between model roughness and rms error.

In this inversion scheme, trade-off parameters between data misfit, model roughness and static shift are estimated so as to minimize the misfit functional, assuming that static shifts have Gaussian distributions.

The aim of the code is to seek minimization of data misfit, model roughness (α1 and α2) and the static shift parameter, simultaneously (α1, α2 and β here should not be confused with the phase tensor parameters presented earlier).

a Trade-off curve (L-curve) between data misfit and model roughness in the coseismic model.

a Trade-off curve (L-curve) between data misfit and model roughness in the postseismic model.

We also calculate a tradeoff curve between the data misfits and model roughness.

The involved objective parameters which led to those results are sharpness, roughness, hearing model roughness ½ Bark, PM1, PM2.5 and PM10.