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Approximation of stochastic invariant manifolds[electronic resource] :stochastic manifolds for nonlinear SPDEs I /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	515.353
書名/作者:	Approximation of stochastic invariant manifolds : stochastic manifolds for nonlinear SPDEs I // by Mickael D. Chekroun, Honghu Liu, Shouhong Wang.
作者:	Chekroun, Mickael D.
其他作者:	Liu, Honghu.
出版者:	Cham : : Springer International Publishing :, 2015.
面頁冊數:	xv, 127 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Stochastic partial differential equations.
標題:	Mathematics.
標題:	Dynamical Systems and Ergodic Theory.
標題:	Partial Differential Equations.
標題:	Probability Theory and Stochastic Processes.
標題:	Ordinary Differential Equations.
ISBN:	9783319124964 (electronic bk.)
ISBN:	9783319124957 (paper)
內容註:	General Introduction -- Stochastic Invariant Manifolds: Background and Main Contributions -- Preliminaries -- Stochastic Evolution Equations -- Random Dynamical Systems -- Cohomologous Cocycles and Random Evolution Equations -- Linearized Stochastic Flow and Related Estimates -- Existence and Attraction Properties of Global Stochastic Invariant Manifolds -- Existence and Smoothness of Global Stochastic Invariant Manifolds -- Asymptotic Completeness of Stochastic Invariant Manifolds -- Local Stochastic Invariant Manifolds: Preparation to Critical Manifolds -- Local Stochastic Critical Manifolds: Existence and Approximation Formulas -- Standing Hypotheses -- Existence of Local Stochastic Critical Manifolds -- Approximation of Local Stochastic Critical Manifolds -- Proofs of Theorem 6.1 and Corollary 6.1 -- Approximation of Stochastic Hyperbolic Invariant Manifolds -- A Classical and Mild Solutions of the Transformed RPDE -- B Proof of Theorem 4.1 -- References.
摘要、提要註:	This first volume is concerned with the analytic derivation of explicit formulas for the leading-order Taylor approximations of (local) stochastic invariant manifolds associated with a broad class of nonlinear stochastic partial differential equations. These approximations take the form of Lyapunov-Perron integrals, which are further characterized in Volume II as pullback limits associated with some partially coupled backward-forward systems. This pullback characterization provides a useful interpretation of the corresponding approximating manifolds and leads to a simple framework that unifies some other approximation approaches in the literature. A self-contained survey is also included on the existence and attraction of one-parameter families of stochastic invariant manifolds, from the point of view of the theory of random dynamical systems.
電子資源:	http://dx.doi.org/10.1007/978-3-319-12496-4

Approximation of stochastic invariant manifolds[electronic resource] :stochastic manifolds for nonlinear SPDEs I /
Chekroun, Mickael D.

Approximation of stochastic invariant manifoldsstochastic manifolds for nonlinear SPDEs I /[electronic resource] :by Mickael D. Chekroun, Honghu Liu, Shouhong Wang. - Cham :Springer International Publishing :2015. - xv, 127 p. :ill., digital ;24 cm. - SpringerBriefs in mathematics,2191-8198. - SpringerBriefs in mathematics..

General Introduction -- Stochastic Invariant Manifolds: Background and Main Contributions -- Preliminaries -- Stochastic Evolution Equations -- Random Dynamical Systems -- Cohomologous Cocycles and Random Evolution Equations -- Linearized Stochastic Flow and Related Estimates -- Existence and Attraction Properties of Global Stochastic Invariant Manifolds -- Existence and Smoothness of Global Stochastic Invariant Manifolds -- Asymptotic Completeness of Stochastic Invariant Manifolds -- Local Stochastic Invariant Manifolds: Preparation to Critical Manifolds -- Local Stochastic Critical Manifolds: Existence and Approximation Formulas -- Standing Hypotheses -- Existence of Local Stochastic Critical Manifolds -- Approximation of Local Stochastic Critical Manifolds -- Proofs of Theorem 6.1 and Corollary 6.1 -- Approximation of Stochastic Hyperbolic Invariant Manifolds -- A Classical and Mild Solutions of the Transformed RPDE -- B Proof of Theorem 4.1 -- References.

This first volume is concerned with the analytic derivation of explicit formulas for the leading-order Taylor approximations of (local) stochastic invariant manifolds associated with a broad class of nonlinear stochastic partial differential equations. These approximations take the form of Lyapunov-Perron integrals, which are further characterized in Volume II as pullback limits associated with some partially coupled backward-forward systems. This pullback characterization provides a useful interpretation of the corresponding approximating manifolds and leads to a simple framework that unifies some other approximation approaches in the literature. A self-contained survey is also included on the existence and attraction of one-parameter families of stochastic invariant manifolds, from the point of view of the theory of random dynamical systems.

ISBN: 9783319124964 (electronic bk.)

Standard No.: 10.1007/978-3-319-12496-4doiSubjects--Topical Terms:

605621
Stochastic partial differential equations.

LC Class. No.: QA274.25

Dewey Class. No.: 515.353

Approximation of stochastic invariant manifolds[electronic resource] :stochastic manifolds for nonlinear SPDEs I /
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520 $a This first volume is concerned with the analytic derivation of explicit formulas for the leading-order Taylor approximations of (local) stochastic invariant manifolds associated with a broad class of nonlinear stochastic partial differential equations. These approximations take the form of Lyapunov-Perron integrals, which are further characterized in Volume II as pullback limits associated with some partially coupled backward-forward systems. This pullback characterization provides a useful interpretation of the corresponding approximating manifolds and leads to a simple framework that unifies some other approximation approaches in the literature. A self-contained survey is also included on the existence and attraction of one-parameter families of stochastic invariant manifolds, from the point of view of the theory of random dynamical systems.
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