Paley-Wiener integral

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In mathematics, the Paley-Wiener integral is a simple stochastic integral. When applied to classical Wiener space, it is less general than the Itō integral, but the two agree when they are both defined.

[edit] Definition

Let i : H \to E be an abstract Wiener space with abstract Wiener measure γ on E. Let j : E^{*} \to H be the adjoint of i. (We have abused notation slightly: strictly speaking, j : E^{*} \to H^{*}, but since H is a Hilbert space, it is isometrically isomorphic to its dual space H * , by the Riesz representation theorem.)

It can be shown that j is injective and has dense image in H. Furthermore, it can be shown that every linear functional \ell \in E^{*} is also square-integrable: in fact,

\| \ell \|_{L^{2} (E, \gamma; \mathbb{R})} = \| j(\ell) \|_{H}

This defines a natural linear map from j(E * ) to L^{2} (E, \gamma; \mathbb{R}), under which j(\ell) \in j(E^{*}) \subseteq H goes to the equivalence class of \ell in L^{2} (E, \gamma; \mathbb{R}). This is well-defined since j is injective. This map is an isometry, so it is continuous.

However, since a continuous linear map between Banach spaces such as H and L^{2} (E, \gamma; \mathbb{R}) is uniquely determined by its values on any dense subspace of its domain, there is a unique continuous linear extension I : H \to L^{2} (E, \gamma; \mathbb{R}) of the above natural map j(\ell) \mapsto [\ell] to the whole of H.

This isometry I : H \to L^{2} (E, \gamma; \mathbb{R}) is known as the Paley-Wiener map. I(h), also denoted \langle h, - \rangle^{\sim}, is a function on E and is known as the Paley-Wiener integral (with respect to h \in H).

It is important to note that the Paley-Wiener integral for a particular element h \in H is a function on E. The notation \langle h, x \rangle^{\sim} does not really denote an inner product (after all, h and x belong to two different spaces), but is a convenient abuse of notation in view of the Cameron-Martin theorem. For this reason, many authors prefer to write \langle h, - \rangle^{\sim} (x) or I(h)(x) rather than using the more compact but potentially confusing \langle h, x \rangle^{\sim} notation.

[edit] See also

Other stochastic integrals: