Euler–Maruyama Method

Version 1.0.0 (199 KB) von Emma Gau
Simulate Brownian particle motion by the Euler–Maruyama method
Aktualisiert 14 Nov 2018

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Anmerkung des Herausgebers: This file was selected as MATLAB Central Pick of the Week

A stochastic differential equation (SDE) aims to relate a stochastic process to its composition of random components and base deterministic function. As the relation process is prolonged over time, solutions arise under an initial condition and boundary conditions. Therefore solutions of stochastic differential equations exist and are unique (see app.). For this simulation, the Euler–Maruyama (EM) method will be used to approximate and simulate standard Brownian particle motion.

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Emma Gau (2024). Euler–Maruyama Method (, MATLAB Central File Exchange. Abgerufen .

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Erstellt mit R2018a
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