The generation of diffusion Markovian processes with probability density function defined on part of the real axis

Author

Kontorovich, Valerii ; Lyandres, Vladimir ; Primak, Sergey

Author_Institution

Centro de Investigacion y de Estudios Avanzados, IPN, Mexico City, Mexico

Volume

3

Issue

1

fYear

1996

Firstpage

19

Lastpage

21

Abstract

The correlated random process is represented as a solution of a stochastic differential first-order equation (SDE). The case of processes with a probability density function defined on a semi-infinite or finite range is considered. The limitation of the range of the simulated process requires modification of the specific structure of the SDE. The approach presented provides excellent results in modeling significant non-Gaussian processes with approximately an exponential correlation function. It is validated by direct numerical simulation of a uniformly distributed correlated process.

Keywords

Markov processes; correlation methods; differential equations; probability; random processes; signal representation; correlated random process; diffusion Markovian processes; exponential correlation function; finite range; nonGaussian processes; numerical simulation; probability density function; real axis; semi-infinite range; simulated process; stochastic differential first-order equation; uniformly distributed correlated process; Density functional theory; Differential equations; Gaussian noise; Gaussian processes; Numerical simulation; Probability density function; Random processes; Stochastic processes;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/97.475826

Filename

475826