
In this note we consider the almost sure convergence (as ϵ→0) of solution Xϵ(·), defined over the interval 0 ≤ τ ≤ 1, of the random ordinary differential equation View the MathML source Here {F(x, t, ω), t ≥ 0} is a strong mixing process for each x and (x, t) → F(x, t, ω) is subject to regularity conditions which ensure the existence of a unique solution over 0 ≤ τ ≤ 1 for all ϵ > 0. Under rather weak conditions it is shown that the function Xϵ(·, ω) converges a.s. to the solution x0(·) of a non-random averaged differential equation View the MathML source the convergence being uniform over 0 ≤ τ ≤ 1.
Strong limit theorems, Ordinary differential equations and systems with randomness, stochastic averaging principle, Applied Mathematics, Applied mathematics, Stochastic ordinary differential equations (aspects of stochastic analysis), strong convergence, FOS: Mathematics, Stochastic averaging principle, random ordinary differential equation, Analysis, Mathematics
Strong limit theorems, Ordinary differential equations and systems with randomness, stochastic averaging principle, Applied Mathematics, Applied mathematics, Stochastic ordinary differential equations (aspects of stochastic analysis), strong convergence, FOS: Mathematics, Stochastic averaging principle, random ordinary differential equation, Analysis, Mathematics
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