Stochastic Partial Differential Equations

Szerző: Sergey Lototsky, Boris L. Rozovsky

Nyelv:

Kötés: Puha kötésű

Kiadó: Springer International Publishing AG

Elérhetőség: Beszállítói készleten

Küldés 5-8 napon belül

30 194 Ft

Taking readers with a basic knowledge of probability and real analysis to the frontiers of a very ac...

Információk a könyvről

Szerző

Sergey Lototsky, Boris L. Rozovsky

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2017

oldal

508

EAN

9783319586458

ISBN

3319586459

Enbook ID

16190218

Kiadó

Springer International Publishing AG

Súly

800

Méretek

159 x 234 x 30

Teljes leírás

Taking readers with a basic knowledge of probability and real analysis to the frontiers of a very active research discipline, this textbook provides all the necessary background from functional analysis and the theory of PDEs. It covers the main types of equations (elliptic, hyperbolic and parabolic) and discusses different types of random forcing. The objective is to give the reader the necessary tools to understand the proofs of existing theorems about SPDEs (from other sources) and perhaps even to formulate and prove a few new ones. Most of the material could be covered in about 40 hours of lectures, as long as not too much time is spent on the general discussion of stochastic analysis in infinite dimensions. As the subject of SPDEs is currently making the transition from the research level to that of a graduate or even undergraduate course, the book attempts to present enough exercise material to fill potential exams and homework assignments. Exercises appear throughout and are usually directly connected to the material discussed at a particular place in the text. The questions usually ask to verify something, so that the reader already knows the answer and, if pressed for time, can move on. Accordingly, no solutions are provided, but there are often hints on how to proceed. The book will be of interest to everybody working in the area of stochastic analysis, from beginning graduate students to experts in the field.

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Stochastic Partial Differential Equations

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