Detail publikace

Simulation of Multiconductor Transmission Lines with Random Parameters via Stochastic Differential Equations Approach.

BRANČÍK, L. KOLÁŘOVÁ, E.

Originální název

Simulation of Multiconductor Transmission Lines with Random Parameters via Stochastic Differential Equations Approach.

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

This article addresses a method for the simulation of multiconductor transmission lines (MTLs) with fluctuating parameters based on the theory of stochastic differential equations (SDEs). Specifically, confidence intervals of an MTL models stochastic responses are effectively evaluated. First, the MTLs deterministic model with lumped parameters, based on generalized PI sections connected in cascade, is formulated and described through a state variable method, which results in a vector ordinary differential equation (ODE) in the time domain. A vector SDE is then developed by incorporating the respective stochastic processes into its deterministic counterpart. Next, the first two moments of the stochastic processes are calculated via the solution of respective Lyapunov-like ODEs, to assess expectations and the variances of stochastic responses, and also to determine relevant confidence intervals. A statistical processing of individual stochastic trajectories is used to validate the results.

Klíčová slova

multiconductor transmission line; random parameter; stochastic differential equation; variance; confidence interval; MATLAB

Autoři

BRANČÍK, L.; KOLÁŘOVÁ, E.

Vydáno

1. 6. 2016

Nakladatel

SAGE Publishing

Místo

London, United Kingdom

ISSN

0037-5497

Periodikum

SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL

Ročník

92

Číslo

6

Stát

Spojené království Velké Británie a Severního Irska

Strany od

521

Strany do

533

Strany počet

13

URL

BibTex

@article{BUT125050,
  author="Lubomír {Brančík} and Edita {Kolářová}",
  title="Simulation of Multiconductor Transmission Lines with Random Parameters via Stochastic Differential Equations Approach.",
  journal="SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL",
  year="2016",
  volume="92",
  number="6",
  pages="521--533",
  doi="10.1177/0037549716645198",
  issn="0037-5497",
  url="http://sim.sagepub.com/content/92/6/521.full.pdf?ijkey=0hH1aBawL74zJaX&keytype=finite"
}