Sentence examples for fitting difference from inspiring English sources

This latter method was originally proposed as an 'exponential fitting' difference scheme by Allen and Southwell in [29] and subsequently referred to as an artificial diffusion stabilized scheme with 'optimal viscosity' by Brooks and Hughes in [18].

Univariate data analysis methods such as first and second order derivatives, curve fitting, difference (e.g. diseased minus normal) spectral analysis, and various bands intensity/area under the curve ratios facilitate the visualization of band shifts, peak broadening, change in intensities etc. [2, 9 11].

c λmax of single mutant C86F calculated from fitting difference spectra of dark and acid denatured species.

The fitting mean difference and standard deviation are x0 = –1.9°, b = 10.4° for 0.34 mm depth and x0 = –0.7°, b = 9.9° for 0.66 mm depth.

Individual data were examined and only large fitting strategy differences were retained.

This paper presents a new high-order shock-fitting finite-difference method for the DNS of the stability and transition of hypersonic boundary layers over blunt bodies with strong bow shocks and with (or without) thermo-chemical nonequilibrium.

Vocal fold fitting uses the same process as vocal tract fitting, with the difference that the residual signal is obtained using LPC analysis, and the spectrum of the residual signal is available to construct the cost function 1 in Figure 10 for vocal fold fitting.

Exponentially fitted finite difference scheme based on Il'in-Allen-Southwell fitting is used on a specially designed mesh.

The red, blue, and black lines show the east west component of the original data, the smoothed data by spline fitting, and their difference (i.e., high-pass filtered data) on the base line set to −6,310 nT, respectively.

The red, blue, and black lines show the east west component of the original data, the smoothed data obtained by spline fitting, and their difference, i.e., the high-pass filtered data on the base line set to −6,310 nT, respectively.

Simply examining the best-fit model may be misleading, because when there are several similarly fitting models small differences in the likelihood may lead to different models being chosen.