1997
DOI: 10.1006/jfan.1996.3091
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Weighted Stochastic Sobolev Spaces and Bilinear SPDEs Driven by Space–Time White Noise

Abstract: In this paper we develop basic elements of Malliavin calculus on a weighted L 2 (0). This class of generalized Wiener functionals is a Hilbert space. It turns out to be substantially smaller than the space of Hida distributions while large enough to accommodate solutions of bilinear stochastic PDEs. As an example, we consider a stochastic advection-diffusion equation driven by space-time white noise in R d . It is known that for d>1, this equation has no solutions in L 2 (0). In contrast, it is shown in the pa… Show more

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Cited by 47 publications
(42 citation statements)
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“…[11,12,25]. For historical remarks regarding other types of generalized solutions and applications to SPDEs see the review paper [18] and the references therein.…”
Section: MMmentioning
confidence: 99%
“…[11,12,25]. For historical remarks regarding other types of generalized solutions and applications to SPDEs see the review paper [18] and the references therein.…”
Section: MMmentioning
confidence: 99%
“…(1) for a log-normal coefficient a(x, x) is square integrable in the probability space, the strong ellipticity still fails since a log-normal random field is not strictly positive from below, which implies that the Lax-Milgram lemma cannot be applied directly. Then we have to study the solution in a space larger than L 2 ðFÞ, where we usually associate a weight either to the probability measure or to each term of the orthonormal basis of the L 2 ðFÞ space [7,12,9,13], see Section 3.2, where F indicates a complete probability space.…”
Section: Introductionmentioning
confidence: 99%
“…Let aðx; xÞ ¼ a2J a a ðxÞH a ðnÞ and a }ðÀ1Þ ðx; xÞ ¼ P a2Jã b ðxÞ-H b ðnÞ. Substituting them into Eq (12). and comparing the coefficients of H a (n), we obtaiñ…”
mentioning
confidence: 97%
“…There have been extensive studies on this model (see e.g. [6,7,8,9,10,11]). In those articles, the authors proved the existence and uniqueness of the solution and studied at greater length the asymptotic behaviors of the solution to (1.1).…”
Section: ∂ ∂T U(t X) = ∆U(t X) + U(t X)ẇ (T X)mentioning
confidence: 99%