On the modeling of linear system input stochastic processes with given accuracy and reliability

DOI10.1515/mcma-2018-0011zbMath1391.60072OpenAlexW2799767282WikidataQ129966299 ScholiaQ129966299MaRDI QIDQ1637517

Mariia Lyzhechko, Iryna V. Rozora

Publication date: 8 June 2018

Published in: Monte Carlo Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/mcma-2018-0011

zbMATH Keywords

simulationGaussian processaccuracy and reliability

Mathematics Subject Classification ID

Related Items (3)

On one way of modeling a stochastic process with given accuracy and reliability ⋮ Construction of the Karhunen–Loève model for an input Gaussian process in a linear system by using the output process ⋮ Conditions for the sample continuity with probability one for square-Gaussian stochastic processes

Cites Work

• First passage Monte Carlo algorithms for solving coupled systems of diffusion-reaction equations
• Comparative analysis of multiscale Gaussian random field simulation algorithms
• Simulation of weakly self-similar stationary increment \(\mathbf{Sub}_\varphi(\Omega)\)-processes: A series expansion approach
• Properties of Some Random Series
• Uniform Convergence of Wavelet Expansions of Gaussian Random Processes
• Statistical hypothesis testing for the shape of impulse response function
• On an expansion of random processes in series
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