Approximation of distribution law of experimental test data to assess reliability of information-measuring and control systems

Methods of approximation for the distribution law of experimental data find wide application in problems of reliability assessment in tests of both hardware and software of software modules of information-measuring and control systems (SM IMCS). Thus, the main task is to solve the problem of increas...

Full description

Saved in:
Bibliographic Details
Published inJournal of physics. Conference series Vol. 1441; no. 1; pp. 12081 - 12088
Main Authors Zyryanov, Yu T, Ryazanov, I G, Naumova, A Yu, Muromtsev, D Yu, Chernyshov, N G, Trapeznikov, E V
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.01.2020
Subjects
Approximation
Control systems
Data processing
Mathematical analysis
Physics
Reliability analysis
Software
Online AccessGet full text

Cover

More Information
Summary:Methods of approximation for the distribution law of experimental data find wide application in problems of reliability assessment in tests of both hardware and software of software modules of information-measuring and control systems (SM IMCS). Thus, the main task is to solve the problem of increasing the accuracy of the approximation and simplify experimental data processing. In this paper various modification types of Pearson distribution for data taking both positive and negative values, and for data taking only positive values are considered. The described modifications allow one to solve a range of problems related to the existing distributions, as well as to improve the simplicity of the approximation procedure. Pearson logarithmic distributions are proposed for experimental data that take only positive values.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1441/1/012081