Statistical analysis of crosstalk subject to multiple uncertainty sources using stochastic reduced order models

This paper presents a novel statistical approach, referred to as the stochastic reduced order model (SROM) method, to predict the statistics of crosstalk in the presence of multiple uncertainty sources. In this paper, the cable is modelled using a three-conductor transmission line, and the SROM meth...

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Bibliographic Details
Published inIEEE International Symposium on Electromagnetic Compatibility (EMC Europe) pp. 690 - 694
Main Authors Zhouxiang Fei, Yi Huang, Jiafeng Zhou, Qian Xu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2016
Subjects
Crosstalk
Electromagnetic compatibility
Input variables
Power cables
Random variables
statistical analysis
Stochastic processes
stochastic reduced order models
Wires
Online AccessGet full text
ISSN2325-0364
DOI10.1109/EMCEurope.2016.7739227

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Summary:This paper presents a novel statistical approach, referred to as the stochastic reduced order model (SROM) method, to predict the statistics of crosstalk in the presence of multiple uncertainty sources. In this paper, the cable is modelled using a three-conductor transmission line, and the SROM method is applied to obtain the statistics of crosstalk subject to two independent uncertain sources. Compared with the conventional Monte Carlo (MC) method, it is found that the SROM method can produce accurate statistics of crosstalk using a small computational cost. The Stochastic Collocation (SC) method is also implemented to validate the efficacy of the SROM method. Since the implementation of the SROM method is non-intrusive, the application of this method to other uncertainty-embedded electromagnetic compatibility (EMC) problems is straightforward.
ISSN:2325-0364
DOI:10.1109/EMCEurope.2016.7739227