Difference between revisions of "Wiener measure(2)"
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− | + | The [[Probability distribution|probability distribution]] of a [[Brownian motion|Brownian motion]] $ B ( t, \omega ) $, | |
+ | $ t \geq 0 $, | ||
+ | $ \omega \in \Omega $, | ||
+ | where $ ( \Omega, {\mathcal B}, {\mathsf P} ) $ | ||
+ | is a [[Probability space|probability space]]. The Wiener measure is denoted by $ m $ | ||
+ | or $ \mu ^ {W} $. | ||
+ | Brownian motion $ B $ | ||
+ | is a [[Gaussian process|Gaussian process]] such that | ||
− | + | $$ | |
+ | {\mathsf E} ( B ( t ) ) \equiv 0, \quad {\mathsf E} ( B ( t ) \cdot B ( s ) ) = \min ( t, s ) . | ||
+ | $$ | ||
− | + | Given a Brownian motion $ B ( t, \omega ) $, | |
+ | one can form a new Brownian motion $ {\overline{B}\; } ( t, \omega ) $ | ||
+ | satisfying: | ||
− | + | i) $ {\overline{B}\; } ( t, \omega ) $ | |
+ | is continuous in $ t $ | ||
+ | for almost all $ \omega $. | ||
− | + | ii) $ {\mathsf P} ( {\overline{B}\; } ( t, \omega ) = B ( t, \omega ) ) = 1 $ | |
+ | for every $ t $. | ||
− | + | Such a process $ {\overline{B}\; } ( t, \omega ) $ | |
+ | is called a continuous version of $ B ( t, \omega ) $. | ||
− | The | + | The Kolmogorov–Prokhorov theorem tells that the probability distribution $ m $ |
+ | of the Brownian motion $ B ( t ) $ | ||
+ | can be introduced in the space $ C = C [ 0, \infty ) $ | ||
+ | of all continuous functions on $ [ 0, \infty ) $. | ||
− | + | Let $ {\mathcal B} $ | |
+ | be the topological Borel field (cf. also [[Borel field of sets|Borel field of sets]]) of subsets of $ C $. | ||
+ | The [[Measure space|measure space]] $ ( C, {\mathcal B}, m ) $ | ||
+ | thus obtained is the Wiener measure space. | ||
− | The | + | The integral of a $ {\mathcal B} $- |
+ | measurable functional on $ C $ | ||
+ | with respect to $ m $ | ||
+ | is defined in the usual manner. (See also [[Stochastic integral|Stochastic integral]].) | ||
− | + | An elementary and important example of a $ {\mathcal B} $- | |
+ | measurable functional of $ y \in C $ | ||
+ | is a stochastic bilinear form, given by $ \langle { {\dot{y} } , f } \rangle $, | ||
+ | where $ f $ | ||
+ | is an $ L _ {2} [ 0, \infty ) $- | ||
+ | function. It is usually denoted by $ f ( y ) $. | ||
+ | It is, in fact, defined by $ - \int _ {0} ^ \infty {y ( t ) {\dot{f} } ( t ) } {dt } $ | ||
+ | for smooth functions $ f $. | ||
+ | For a general $ f $, | ||
+ | $ f ( y ) $ | ||
+ | can be approximated by stochastic bilinear forms defined by smooth functions $ f $. | ||
+ | An integral of this type is called a Wiener integral. Under certain restrictions, such as non-anticipation, the integral can be extended to the case where the integrand is a functional of $ t $ | ||
+ | and $ y $. | ||
+ | And an even more general case has been proposed. | ||
− | The | + | The class of general (non-linear) functionals of $ y $ |
+ | is introduced as follows. Let $ H $ | ||
+ | be the [[Hilbert space|Hilbert space]] of all complex-valued, square- $ m $- | ||
+ | integrable functionals on $ C $. | ||
+ | Then, $ H $ | ||
+ | admits a direct sum decomposition ([[Fock space|Fock space]]) | ||
− | + | $$ | |
+ | H = \oplus _ { n } {\mathcal H} _ {n} . | ||
+ | $$ | ||
− | where | + | The subspace $ {\mathcal H} _ {n} $ |
+ | is spanned by the Fourier–Hermite polynomials of degree $ n $, | ||
+ | which are of the form | ||
+ | |||
+ | $$ | ||
+ | \prod _ { j } H _ {n _ {j} } \left ( { | ||
+ | \frac{\left \langle {y,f _ {j} } \right \rangle }{\sqrt 2 } | ||
+ | } \right ) , | ||
+ | $$ | ||
+ | |||
+ | where $ \Sigma n _ {j} = n $ | ||
+ | and $ \{ f _ {j} \} $ | ||
+ | is a complete [[Orthonormal system|orthonormal system]] in the Hilbert space $ L _ {2} [ 0, \infty ) $. | ||
+ | The space $ H _ {n} $ | ||
+ | can be interpreted as the space of multiple Wiener integrals of degree $ n $, | ||
+ | due to K. Itô. | ||
====References==== | ====References==== | ||
<table><TR><TD valign="top">[a1]</TD> <TD valign="top"> R. Cameron, W.T. Martin, "The orthogonal development of non-linear functionals in series of Fourier–Hermite functionals" ''Ann. of Math. (2)'' , '''48''' pp. 385–392</TD></TR><TR><TD valign="top">[a2]</TD> <TD valign="top"> T. Hida, "Brownian motion" , ''Applications of Mathematics'' , '''11''' , Springer (1980)</TD></TR></table> | <table><TR><TD valign="top">[a1]</TD> <TD valign="top"> R. Cameron, W.T. Martin, "The orthogonal development of non-linear functionals in series of Fourier–Hermite functionals" ''Ann. of Math. (2)'' , '''48''' pp. 385–392</TD></TR><TR><TD valign="top">[a2]</TD> <TD valign="top"> T. Hida, "Brownian motion" , ''Applications of Mathematics'' , '''11''' , Springer (1980)</TD></TR></table> |
Latest revision as of 08:29, 6 June 2020
The probability distribution of a Brownian motion $ B ( t, \omega ) $,
$ t \geq 0 $,
$ \omega \in \Omega $,
where $ ( \Omega, {\mathcal B}, {\mathsf P} ) $
is a probability space. The Wiener measure is denoted by $ m $
or $ \mu ^ {W} $.
Brownian motion $ B $
is a Gaussian process such that
$$ {\mathsf E} ( B ( t ) ) \equiv 0, \quad {\mathsf E} ( B ( t ) \cdot B ( s ) ) = \min ( t, s ) . $$
Given a Brownian motion $ B ( t, \omega ) $, one can form a new Brownian motion $ {\overline{B}\; } ( t, \omega ) $ satisfying:
i) $ {\overline{B}\; } ( t, \omega ) $ is continuous in $ t $ for almost all $ \omega $.
ii) $ {\mathsf P} ( {\overline{B}\; } ( t, \omega ) = B ( t, \omega ) ) = 1 $ for every $ t $.
Such a process $ {\overline{B}\; } ( t, \omega ) $ is called a continuous version of $ B ( t, \omega ) $.
The Kolmogorov–Prokhorov theorem tells that the probability distribution $ m $ of the Brownian motion $ B ( t ) $ can be introduced in the space $ C = C [ 0, \infty ) $ of all continuous functions on $ [ 0, \infty ) $.
Let $ {\mathcal B} $ be the topological Borel field (cf. also Borel field of sets) of subsets of $ C $. The measure space $ ( C, {\mathcal B}, m ) $ thus obtained is the Wiener measure space.
The integral of a $ {\mathcal B} $- measurable functional on $ C $ with respect to $ m $ is defined in the usual manner. (See also Stochastic integral.)
An elementary and important example of a $ {\mathcal B} $- measurable functional of $ y \in C $ is a stochastic bilinear form, given by $ \langle { {\dot{y} } , f } \rangle $, where $ f $ is an $ L _ {2} [ 0, \infty ) $- function. It is usually denoted by $ f ( y ) $. It is, in fact, defined by $ - \int _ {0} ^ \infty {y ( t ) {\dot{f} } ( t ) } {dt } $ for smooth functions $ f $. For a general $ f $, $ f ( y ) $ can be approximated by stochastic bilinear forms defined by smooth functions $ f $. An integral of this type is called a Wiener integral. Under certain restrictions, such as non-anticipation, the integral can be extended to the case where the integrand is a functional of $ t $ and $ y $. And an even more general case has been proposed.
The class of general (non-linear) functionals of $ y $ is introduced as follows. Let $ H $ be the Hilbert space of all complex-valued, square- $ m $- integrable functionals on $ C $. Then, $ H $ admits a direct sum decomposition (Fock space)
$$ H = \oplus _ { n } {\mathcal H} _ {n} . $$
The subspace $ {\mathcal H} _ {n} $ is spanned by the Fourier–Hermite polynomials of degree $ n $, which are of the form
$$ \prod _ { j } H _ {n _ {j} } \left ( { \frac{\left \langle {y,f _ {j} } \right \rangle }{\sqrt 2 } } \right ) , $$
where $ \Sigma n _ {j} = n $ and $ \{ f _ {j} \} $ is a complete orthonormal system in the Hilbert space $ L _ {2} [ 0, \infty ) $. The space $ H _ {n} $ can be interpreted as the space of multiple Wiener integrals of degree $ n $, due to K. Itô.
References
[a1] | R. Cameron, W.T. Martin, "The orthogonal development of non-linear functionals in series of Fourier–Hermite functionals" Ann. of Math. (2) , 48 pp. 385–392 |
[a2] | T. Hida, "Brownian motion" , Applications of Mathematics , 11 , Springer (1980) |
Wiener measure(2). Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Wiener_measure(2)&oldid=49221