PROBABILISTIC-STATISTICAL METHODS FOR DETERMINING THEADSORPTION PEAK DESCRIBED BY THE GAUSS FUNCTION
Abstract
The paper reports probability-statistical methods of determination of adsorption peak described by the Gaussian function. The following are presented: diagram of peak determination on excess adsorption functions pertinent to some advance given threshold values; the particularities of the determination of the end peak. As a result, after finding of the extremum peak in accordance with methods on determination of the start point and the end point we obtain the inaccuracy G, three thresholds are set, i.e., 2G, 3G and 4G, respectively. If and when signal about presence of the end does not enter before moment 4G, that curve value in this moment is taken for the end peak. At arrival of the signal, corresponding to end peak for time less than 2 , device gives the signal on PC that he calculated the area on subroutine, taking into account merged spades (peaks). At the time of arrivals of the signal before importance of time 3 curve value is taken for the end at moment 3 . In interval between 3 and 4 moments of the arrival the end is taken for true end. If and when signal about presence of end peak does not enter before moment 4 , that curve value in this moment is taken for the end peak. Greater accuracy of the determination end peak is obtained due to this introduction that accordingly enlarges accuracy of the processing to whole information range. Thus, we obtain greater accuracy of the determination of the end peak that accordingly enlarges accuracy of information handling at determination of adsorption peak described by Gaussian function.
First Page
56
Last Page
62
DOI
https://doi.org/10.51346/tstu-01.19.3.-77-0033
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Recommended Citation
Abidova, G.Sh.; Aminov, N.Sh.; and Аvdyakovа, О.S.
(2019)
"PROBABILISTIC-STATISTICAL METHODS FOR DETERMINING THEADSORPTION PEAK DESCRIBED BY THE GAUSS FUNCTION,"
Technical science and innovation: Vol. 2019:
Iss.
3, Article 4.
DOI: https://doi.org/10.51346/tstu-01.19.3.-77-0033
Available at:
https://btstu.researchcommons.org/journal/vol2019/iss3/4