Representation of Manifolds for the Stochastic Swift-Hohenberg Equation with Multiplicative Noise
Joint Authors
Source
Advances in Mathematical Physics
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-08
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Representation of approximation for manifolds of the stochastic Swift-Hohenberg equation with multiplicative noise has been investigated via non-Markovian reduced system.
The approximate parameterizations of the small scales for the large scales are given in the process of seeking for stochastic parameterizing manifolds, which are obtained as pullback limits of some backward-forward systems depending on the time-history of the dynamics of the low modes in a mean square sense through the nonlinear terms.
When the corresponding pullback limits of some backward-forward systems are efficiently determined, the corresponding non-Markovian reduced systems can be obtained for researching good modeling performances in practice.
American Psychological Association (APA)
Guo, Yanfeng& Li, D. L.. 2020. Representation of Manifolds for the Stochastic Swift-Hohenberg Equation with Multiplicative Noise. Advances in Mathematical Physics،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1127333
Modern Language Association (MLA)
Guo, Yanfeng& Li, D. L.. Representation of Manifolds for the Stochastic Swift-Hohenberg Equation with Multiplicative Noise. Advances in Mathematical Physics No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1127333
American Medical Association (AMA)
Guo, Yanfeng& Li, D. L.. Representation of Manifolds for the Stochastic Swift-Hohenberg Equation with Multiplicative Noise. Advances in Mathematical Physics. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1127333
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1127333