Two-Dimensional Filtering Method Using Systems of Local Model Functions for Muonogram Analysis

被引：2

作者：

Getmanov, V. G. ^{[1
,2
]}

Sidorov, R., V ^{[1
]}

Dobrovolsky, M. N. ^{[1
]}

Yashin, I. I. ^{[3
]}

Dmitrieva, A. N. ^{[3
]}

Perederin, F., V ^{[2
]}

机构：

[1] Russian Acad Sci, Geophys Ctr, Moscow 119296, Russia

[2] Russian Acad Sci, Inst Phys Earth, Moscow 123242, Russia

[3] Natl Res Nucl Univ MEPhI, Moscow 115409, Russia

来源：

PATTERN RECOGNITION AND IMAGE ANALYSIS | 2020年 / 30卷 / 03期

关键词：

two-dimensional filtering; noise; observations; muonograms; approximation; local models; weighted averaging; statistical modeling;

D O I：

10.1134/S1054661820030062

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A two-dimensional filtering method, based on the construction of systems of approximating sliding local model functions with their subsequent weighted averaging, is proposed. A two-dimensional filtering algorithm based on the summation of approximating sliding piecewise-linear model functions with weight coefficients is developed. Optimization of the parameters of the filtering algorithm is considered. The results of testing the filtering algorithm and calculating its optimal parameters on model muonograms are presented. A comparative estimation of the algorithm's errors is made. An example of testing the developed method of two-dimensional filtering on an experimental muonogram is presented; the results of the muonogram's analysis are described.

引用

页码：460 / 469

页数：10

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