Numerical Generation of Compound Random Processes with an Arbitrary Autocorrelation Function

DIma Bykhovsky, Tom Trigano

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The generation of non-Gaussian random processes with a given autocorrelation function (ACF) is addressed. The generation is based on a compound process with two components. Both components are solutions of appropriate stochastic differential equations (SDEs). One of the components is a Gaussian process and the other one is non-Gaussian with an exponential ACF. The analytical study shows that a compound combination of these processes may be used for the generation of a non-Gaussian random process with a required ACF. The results are verified by two numerical examples.

Original languageEnglish
Article number1850001
JournalFluctuation and Noise Letters
Volume17
Issue number1
DOIs
StatePublished - 1 Mar 2018
Externally publishedYes

Keywords

  • Random process
  • arbitrary auto-correlation function
  • non-Gaussian process
  • product distribution
  • stochastic differential equation (SDE)

ASJC Scopus subject areas

  • Mathematics (all)
  • Physics and Astronomy (all)

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