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Probability Theory and Related Fields
Article . 1994 . Peer-reviewed
License: Springer TDM
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zbMATH Open
Article . 1994
Data sources: zbMATH Open
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Attractors for random dynamical systems

Authors: FLANDOLI FRANCO; Hans Crauel;

Attractors for random dynamical systems

Abstract

Random dynamical systems are treated, the notions of an omega limit set, a random invariant set, an absorbing set and a global attractor are introduced. Conditions are given under which a global attractor (being a compact random invariant set) exists, and some of its properties are established. The theory is then applied to a reaction-diffusion equation with additive noise and to the stochastic Navier-Stokes equation with multiplicative, resp. additive noise. In all the three cases the existence of a compact stochastic attractor is proved.

Country
Italy
Keywords

Attractors and repellers of smooth dynamical systems and their topological structure, global attractor, Ergodic theory, absorbing set, stochastic Navier-Stokes equation, random dynamical systems, omega limit set, Reaction-diffusion equations, Stochastic partial differential equations (aspects of stochastic analysis), reaction-diffusion equation, Navier-Stokes equations, random invariant set

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    692
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
692
Top 0.1%
Top 0.1%
Top 10%
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