New stochastic modeling and analysis method for transmission lines in the presence of random process variations

Ying Zhang, Janet M. Wang, Liang Xiao, Hui Zhong Wu

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The random variations of technological parameters are always existent during manufacturing, which have a definite impact on transmission performance of transmission lines. Considering the impact, the stochastic model for transmission lines is proposed, and the precise integration algorithm is combined with Monte Carlo method to analyze the transient response of the stochastic model. Jarque-Bera test is made for the normality of the model's output and the worst-case estimation is given. In the case of sinusoidal excitation, lossless transmission lines are considered. The analytic form of first moment of the corresponding stochastic differential equation's solution is derived, and the numerical computation method for second moment is given, finally the upper and lower bound of the output signal's amplitude and phase shift is estimated. Experimental results demonstrate that the proposed stochastic model and the statistical analysis method can evaluate the transmission performance of transmission lines effectively.

Original languageEnglish (US)
Pages (from-to)1959-1964
Number of pages6
JournalTien Tzu Hsueh Pao/Acta Electronica Sinica
Volume33
Issue number11
StatePublished - Nov 2005

Keywords

  • Monte Carlo Method
  • Stochastic difference equation
  • Stochastic modeling
  • Telegrapher's equation
  • Transmission line

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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