On the numerical generation of positive-axis-defined distributions with an exponential autocorrelation function

Dima Bykhovsky, Vladimir Lyandres

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Stochastic modeling commonly requires random process generation with an exponential autocorrelation function (ACF). These random processes may be represented as a solution of a stochastic differential equation (SDE) of the first order and usually have one-sided (positive-axis-defined) distributions. However, adoption of the SDE-based method faces serious limitations due to difficulties with the numerical solution. To overcome this issue we propose a tractable general numerical solution of the above-mentioned SDE that preserves solution positivity and accuracy, and validate it with numerical simulations.

Original languageEnglish
Pages (from-to)43-47
Number of pages5
JournalDigital Signal Processing: A Review Journal
Volume77
DOIs
StatePublished - 1 Jun 2018
Externally publishedYes

Keywords

  • Exponential autocorrelation
  • Half-normal distribution
  • Numerical generation of random process
  • Stochastic differential equation
  • χ distribution

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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