- Retrait gratuit dans votre magasin Club
- 7.000.000 titres dans notre catalogue
- Payer en toute sécurité
- Toujours un magasin près de chez vous
- Retrait gratuit dans votre magasin Club
- 7.000.000 titres dans notre catalogue
- Payer en toute sécurité
- Toujours un magasin près de chez vous
Stochastic Parameterizing Manifolds and Non-Markovian Reduced Equations
Stochastic Manifolds for Nonlinear Spdes II
Mickaël D Chekroun, Honghu Liu, Shouhong Wang
52,95 €
+ 105 points
Description
In this second volume, a general approach is developed to provide approximate parameterizations of the "small" scales by the "large" ones for a broad class of stochastic partial differential equations (SPDEs). This is accomplished via the concept of parameterizing manifolds (PMs), which are stochastic manifolds that improve, for a given realization of the noise, in mean square error the partial knowledge of the full SPDE solution when compared to its projection onto some resolved modes. Backward-forward systems are designed to give access to such PMs in practice. The key idea consists of representing the modes with high wave numbers as a pullback limit depending on the time-history of the modes with low wave numbers. Non-Markovian stochastic reduced systems are then derived based on such a PM approach. The reduced systems take the form of stochastic differential equations involving random coefficients that convey memory effects. The theory is illustrated on a stochastic Burgers-type equation.
Spécifications
Parties prenantes
- Auteur(s) :
- Editeur:
Contenu
- Nombre de pages :
- 129
- Langue:
- Anglais
- Collection :
Caractéristiques
- EAN:
- 9783319125190
- Date de parution :
- 14-01-15
- Format:
- Livre broché
- Format numérique:
- Trade paperback (VS)
- Dimensions :
- 156 mm x 234 mm
- Poids :
- 217 g
