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

Zhouxiang Fei, Yi Huang, Jiafeng Zhou, Qian Xu

Research output: Contribution to conferencePaper

Abstract

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.
Original languageEnglish
Number of pages5
DOIs
Publication statusPublished - 10 Nov 2016
Event2016 International Symposium on Electromagnetic Compatibility - EMC EUROPE -
Duration: 5 Sep 2016 → …

Conference

Conference2016 International Symposium on Electromagnetic Compatibility - EMC EUROPE
Period5/09/16 → …

Keywords

  • crosstalk
  • electromagnetic compatibility
  • statistical analysis
  • stochastic reduced order models (SROM)
  • power cables
  • stochastic processes
  • random variables
  • electromagnetic interference

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