Numerical Generation of Compound Random Processes with an Arbitrary Autocorrelation Function

DIma Bykhovsky; Tom Trigano

doi:10.1142/S0219477518500013

Numerical Generation of Compound Random Processes with an Arbitrary Autocorrelation Function

DIma Bykhovsky, Tom Trigano

Research output: Contribution to journal › Article › peer-review

3 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 language	English
Article number	1850001
Journal	Fluctuation and Noise Letters
Volume	17
Issue number	1
DOIs	https://doi.org/10.1142/S0219477518500013
State	Published - 1 Mar 2018
Externally published	Yes

Keywords

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

ASJC Scopus subject areas

General Mathematics
General Physics and Astronomy

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10.1142/S0219477518500013

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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.",

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AB - 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.

KW - Random process

KW - arbitrary auto-correlation function

KW - non-Gaussian process

KW - product distribution

KW - stochastic differential equation (SDE)

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Numerical Generation of Compound Random Processes with an Arbitrary Autocorrelation Function

Abstract

Keywords

ASJC Scopus subject areas

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