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A Concise Course on Stochastic Partial Differential Equations / by Claudia Prévôt, Michael Röckner.

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Math/Physics/Astronomy Library QA3 .L28 v.1-999 470,523,830,849:2nd ed. v.1000-1722,1762,1781,1799-2099,2100-2192-2218 2219-2223-2258,2260-2271,2273-2274-2277,2279-2281,2283-2289,2291,2293-2294,2296,2298-2299,2300-2311,2313-2379,2381-2383 2385,2388-2389
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Format:
Book
Author/Creator:
Prévôt, Claudia, author.
Röckner, Michael, 1956- author.
Contributor:
SpringerLink (Online service)
Series:
Lecture Notes in Mathematics, 0075-8434 ; 1905.
Lecture Notes in Mathematics, 0075-8434 ; 1905
Language:
English
Subjects (All):
Global analysis (Mathematics).
Differential equations, Partial.
Distribution (Probability theory).
Analysis.
Partial Differential Equations.
Probability Theory and Stochastic Processes.
Local Subjects:
Analysis.
Partial Differential Equations.
Probability Theory and Stochastic Processes.
Physical Description:
1 online resource (VI, 148 pages).
Contained In:
Springer eBooks
Place of Publication:
Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.
System Details:
text file PDF
Summary:
These lectures concentrate on (nonlinear) stochastic partial differential equations (SPDE) of evolutionary type. All kinds of dynamics with stochastic influence in nature or man-made complex systems can be modelled by such equations. To keep the technicalities minimal we confine ourselves to the case where the noise term is given by a stochastic integral w.r.t. a cylindrical Wiener process.But all results can be easily generalized to SPDE with more general noises such as, for instance, stochastic integral w.r.t. a continuous local martingale. There are basically three approaches to analyze SPDE: the "martingale measure approach", the "mild solution approach" and the "variational approach". The purpose of these notes is to give a concise and as self-contained as possible an introduction to the "variational approach". A large part of necessary background material, such as definitions and results from the theory of Hilbert spaces, are included in appendices.
Contents:
Motivation, Aims and Examples
Stochastic Integral in Hilbert spaces
Stochastic Differential Equations in Finite Dimensions
A Class of Stochastic Differential Equations in Banach Spaces
Appendices: The Bochner Integral
Nuclear and Hilbert-Schmidt Operators
Pseudo Invers of Linear Operators
Some Tools from Real Martingale Theory
Weak and Strong Solutions: the Yamada-Watanabe Theorem
Strong, Mild and Weak Solutions.
Other Format:
Printed edition:
ISBN:
9783540707813
Access Restriction:
Restricted for use by site license.

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