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 language | English |
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Pages (from-to) | 43-47 |
Number of pages | 5 |
Journal | Digital Signal Processing: A Review Journal |
Volume | 77 |
DOIs | |
State | Published - 1 Jun 2018 |
Externally published | Yes |
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