Generation of strongly non-Gaussian stochastic processes by iterative scheme upgrading phase and amplitude contents

DOI10.1016/J.APM.2020.06.029zbMath1481.62068OpenAlexW3036616393MaRDI QIDQ2049846

Houle Zhang, Yu-feng Gao, Yong-xin Wu

Publication date: 27 August 2021

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2020.06.029

zbMATH Keywords

random errorspectral representation methodnon-Gaussian processcrossing ratetranslation process theory

Mathematics Subject Classification ID

Inference from stochastic processes and spectral analysis (62M15) Probabilistic models, generic numerical methods in probability and statistics (65C20)

Cites Work

• Unnamed Item
• A novel fractional moments-based maximum entropy method for high-dimensional reliability analysis
• Analytical solution for a finite Euler-Bernoulli beam with single discontinuity in section under arbitrary dynamic loads
• Novel algorithm for reconstruction of a distribution by fitting its first-four statistical moments

This page was built for publication: Generation of strongly non-Gaussian stochastic processes by iterative scheme upgrading phase and amplitude contents