Stochastic parameterizing manifolds and non-markovian reduced equations : stochastic manifolds for nonlinear SPDEs II
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The work Stochastic parameterizing manifolds and non-markovian reduced equations : stochastic manifolds for nonlinear SPDEs II represents a distinct intellectual or artistic creation found in University of Liverpool. This resource is a combination of several types including: Work, Language Material, Books.
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Stochastic parameterizing manifolds and non-markovian reduced equations : stochastic manifolds for nonlinear SPDEs II
Resource Information
The work Stochastic parameterizing manifolds and non-markovian reduced equations : stochastic manifolds for nonlinear SPDEs II represents a distinct intellectual or artistic creation found in University of Liverpool. This resource is a combination of several types including: Work, Language Material, Books.
- Label
- Stochastic parameterizing manifolds and non-markovian reduced equations : stochastic manifolds for nonlinear SPDEs II
- Title remainder
- stochastic manifolds for nonlinear SPDEs II
- Statement of responsibility
- Mickaël D. Chekroun, Honghu Liu, Shouhong Wang
- Language
- eng
- Summary
- 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
- Cataloging source
- N$T
- Dewey number
- 515/.353
- Illustrations
- illustrations
- Index
- index present
- LC call number
- QA274.25
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- bibliography
- Series statement
- SpringerBriefs in Mathematics,
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- Stochastic parameterizing manifolds and non-markovian reduced equations : stochastic manifolds for nonlinear SPDEs II, Mickaël D. Chekroun, Honghu Liu, Shouhong Wang, (electronic book)
- Stochastic parameterizing manifolds and non-markovian reduced equations : stochastic manifolds for nonlinear SPDEs II, Mickaël D. Chekroun, Honghu Liu, Shouhong Wang, (electronic book)
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/resource/Ai-XPqAS60k/" typeof="CreativeWork http://bibfra.me/vocab/lite/Work"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/resource/Ai-XPqAS60k/">Stochastic parameterizing manifolds and non-markovian reduced equations : stochastic manifolds for nonlinear SPDEs II</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>