CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Approximating Stationary Statistical Properties
Authors
Xiaoming Wang
Publication date
1 December 2009
Publisher
Scholars\u27 Mine
Abstract
It is well-known that physical laws for large chaotic dynamical systems are revealed statistically. Many times these statistical properties of the system must be approximated numerically. the main contribution of this manuscript is to provide simple and natural criterions on numerical methods (temporal and spatial discretization) that are able to capture the stationary statistical properties of the underlying dissipative chaotic dynamical systems asymptotically. the result on temporal approximation is a recent finding of the author, and the result on spatial approximation is a new one. Applications to the infinite Prandtl number model for convection and the barotropic quasi-geostrophic model are also discussed. © Editorial Office of CAM and Springer-Verlag Berlin Heidelberg 2009
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Missouri University of Science and Technology (Missouri S&T): Scholars' Mine
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:scholarsmine.mst.edu:math_...
Last time updated on 29/03/2023