Effective Dynamics of Stochastic Partial Differential Equations
- 1st Edition - February 27, 2014
- Latest edition
- Authors: Jinqiao Duan, Wei Wang
- Language: English
Effective Dynamics of Stochastic Partial Differential Equations focuses on stochastic partial differential equations with slow and fast time scales, or large and small spatial sc… Read more
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Description
Description
Effective Dynamics of Stochastic Partial Differential Equations focuses on stochastic partial differential equations with slow and fast time scales, or large and small spatial scales. The authors have developed basic techniques, such as averaging, slow manifolds, and homogenization, to extract effective dynamics from these stochastic partial differential equations.
The authors’ experience both as researchers and teachers enable them to convert current research on extracting effective dynamics of stochastic partial differential equations into concise and comprehensive chapters. The book helps readers by providing an accessible introduction to probability tools in Hilbert space and basics of stochastic partial differential equations. Each chapter also includes exercises and problems to enhance comprehension.
Key features
Key features
- New techniques for extracting effective dynamics of infinite dimensional dynamical systems under uncertainty
- Accessible introduction to probability tools in Hilbert space and basics of stochastic partial differential equations
- Solutions or hints to all Exercises
Readership
Readership
Students in applied mathematics and professionals in the sciences and engineering community need to deal with stochastic models
Table of contents
Table of contents
Cover image
Dedication
Preface
1: Introduction
1.1 Motivation
1.2 Examples of Stochastic Partial Differential Equations
1.3 Outlines for This Book
2: Deterministic Partial Differential Equations
2.1 Fourier Series in Hilbert Space
2.2 Solving Linear Partial Differential Equations
2.3 Integral Equalities
2.4 Differential and Integral Inequalities
2.5 Sobolev Inequalities
2.6 Some Nonlinear Partial Differential Equations
2.7 Problems
3: Stochastic Calculus in Hilbert Space
3.1 Brownian Motion and White Noise in Euclidean Space
3.2 Deterministic Calculus in Hilbert Space
3.3 Random Variables in Hilbert Space
3.4 Gaussian Random Variables in Hilbert Space
3.5 Brownian Motion and White Noise in Hilbert Space
3.6 Stochastic Calculus in Hilbert Space
3.7 Itô’s Formula in Hilbert Space
3.8 Problems
4: Stochastic Partial Differential Equations
4.1 Basic Setup
4.2 Strong and Weak Solutions
4.3 Mild Solutions
4.4 Martingale Solutions
4.5 Conversion Between Itô and Stratonovich SPDEs
4.6 Linear Stochastic Partial Differential Equations
4.7 Effects of Noise on Solution Paths
4.8 Large Deviations for SPDEs
4.9 Infinite Dimensional Stochastic Dynamics
4.10 Random Dynamical Systems Defined by SPDEs
4.11 Problems
5: Stochastic Averaging Principles
5.1 Classical Results on Averaging
5.2 An Averaging Principle for Slow-Fast SPDEs
5.3 Proof of the Averaging Principle
5.4 A Normal Deviation Principle for Slow-Fast SPDEs
5.5 Proof of the Normal Deviation Principle
5.6 Macroscopic Reduction for Stochastic Systems
5.7 Large Deviation Principles for the Averaging Approximation
5.8 PDEs with Random Coefficients
5.9 Further Remarks
5.10 Looking Forward
5.11 Problems
6: Slow Manifold Reduction
6.1 Background
6.2 Random Center-Unstable Manifolds for Stochastic Systems
6.3 Random Center-Unstable Manifold Reduction
6.4 Local Random Invariant Manifold for SPDEs
6.5 Random Slow Manifold Reduction for Slow-Fast SPDEs
6.6 A Different Reduction Method for SPDEs: Amplitude Equation
6.7 Looking Forward
6.8 Problems
7: Stochastic Homogenization
7.1 Deterministic Homogenization
7.2 Homogenized Macroscopic Dynamics for Stochastic Linear Microscopic Systems
7.3 Homogenized Macroscopic Dynamics for Stochastic Nonlinear Microscopic Systems
7.4 Looking Forward
7.5 Problems
Hints and Solutions
Notations
References
Review quotes
Review quotes
Product details
Product details
- Edition: 1
- Latest edition
- Published: February 27, 2014
- Language: English
About the authors
About the authors
JD
Jinqiao Duan
WW