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A discretized paths-based sequential integration method involving the self-similarity of the fractional Brownian motion

Academic Article
Publication Date:
2025
Short description:
A discretized paths-based sequential integration method involving the self-similarity of the fractional Brownian motion / Andrea, B., Di Paola, M., Failla, G., Spanos, P.D.. - In: PROBABILISTIC ENGINEERING MECHANICS. - ISSN 0266-8920. - 80:(2025), p. 103767. [10.1016/j.probengmech.2025.103767]
abstract:
The discretized paths-based sequential integration method (SIM) is a quite versatile approach for solving various problems, including barrier problems, first passage problems, reflecting barrier problems and so on. This method builds upon the Chapman–Kolmogorov equation and is not applicable to non-Markovian problems, as in the case of fractional Brownian motion (FBM). In this paper, it is shown that the loss of the Markovian property can be overcome by utilizing the self-similarity of the FBM. In order to apply the discretized paths-based SIM, we have to solve a specific stochastic boundary value problem, also called stochastic “bridge” problem, which involves selecting only the trajectories of the FBM that ends at an assigned value, say x̄ at tk, at the beginning of the time interval tk−tk+1. It is shown that, due to self-similarity, the stochastic “bridge” problem may be solved only once, regardless of the value x̄ at tk. It is also shown that the trajectories of the stochastic “bridge” problem exhibit self-similarity, which circumvents the loss of Markovian property in FBM, thus allowing the discretized paths-based SIM to be employed without invoking the classical Chapman–Kolmogorov equation. Further, an application involving the classical first passage problem is presented.
Iris type:
1.1 Articolo in rivista
List of contributors:
Andrea, Burlon; Di Paola, Mario; Failla, Giuseppe; Spanos, Pol D.
Authors of the University:
FAILLA Giuseppe
Handle:
https://iris.unirc.it/handle/20.500.12318/167550
Published in:
PROBABILISTIC ENGINEERING MECHANICS
Journal
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https://www.sciencedirect.com/science/article/pii/S0266892025000396
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