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Filtration des ponts browniens et équations différentielles stochastiques linéaires. (Filtering of Brownian bridges and linear stochastic differential equations). (French) Zbl 0699.60075
Séminaire de probabilités XXIV 1988/89, Lect. Notes Math. 1426, 227-265 (1990).
[For the entire collection see Zbl 0695.00024.]
After some preliminaries about enlargements and reductions of filtrations, the authors study the filtration of the Brownian bridge. If $$(X_ t)_{t\geq 0}$$ is a one-dimensional Brownian motion, starting from zero, $$\tilde X_ t=X_ t-\int^{t}_{0}s^{-1}X_ sds$$ is another Brownian; therefore, the application $$T: X\to \tilde X$$ preserves the Wiener measure. With the help of Laguerre polynomials, it is shown that T is strongly mixing.
More generally, the authors consider Gaussian processes defined by: $\beta_ t^{\phi}=B_ t-\int^{t}_{0}\phi (s)B_ sds$ where $$\phi$$ is a Borel function from $${\mathbb{R}}^+$$ to $${\mathbb{R}}$$ such that: $\forall t>0,\quad \int^{t}_{0}| \phi (s)| \sqrt{s}ds<+\infty;$ properties of the filtration of $$\beta_ t^{\phi}$$ are given. Finally, the paper contains a detailed study of the linear stochastic differential equation $X_ t=B_ t+\int^{t}_{0}\phi (s)X_ sds,$ where $$B_ t$$ is a Brownian motion. Existence and uniqueness of solutions are stated under some suitable conditions.
Reviewer: M.Chaleyat-Maurel

MSC:
 60J65 Brownian motion 60H10 Stochastic ordinary differential equations (aspects of stochastic analysis)
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