Sentence examples for linear background estimation from inspiring English sources

The overall linear background estimation (DC) fit, is done using a wider temporal window of samples to achieve best background estimation.

The temporal processing algorithm is based on a comparison of the sub-profile overall linear background estimation (defined as DC) to the single highest fluctuation within the sub-profile.

In PyMca the statistics-sensitive non-linear iterative peak-clipping (SNIP) was chosen as background estimation.

The background estimation is performed by calculating a linear fit by means of least squares estimation (LSE) [21].

Figure 1 The results of background estimation.

The experimental site, detector design, and background estimation are presented.

ROI detection may be done using background subtraction schemes with change detection and background estimation.

Kalman filter is used for adaptive background estimation in [7].

First of all, background estimation is computed recursively (19).

Other approaches based on multiple background estimations [9] or adaptive background estimation [10] have also been proposed.

A linear background was also included in the fit.