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doi: 10.1007/bf01193705
handle: 11568/25797 , 11384/69104
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.
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
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
citations 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). | 750 | |
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. | Top 0.1% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 0.1% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |