Stochastic Partial Differential Equations

Edition en anglais

Note moyenne 
Taking readers with a basic knowledge of probability and real analysis to the frontiers of a very active research discipline, this textbook provides all... Lire la suite
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Résumé

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 4o 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.

Caractéristiques

  • Date de parution
    01/03/2017
  • Editeur
  • Collection
  • ISBN
    978-3-319-58645-8
  • EAN
    9783319586458
  • Présentation
    Broché
  • Nb. de pages
    508 pages
  • Poids
    0.805 Kg
  • Dimensions
    15,5 cm × 23,5 cm × 2,8 cm

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À propos des auteurs

Sergey Lototsky earned his Master's degree in Physics from the Moscow Institute of Physics and Technology, followed by a PhD in Applied Mathematics from the University of Southern California. After four years at MIT, he returned to the department of Mathematics at USC, where he specializes in stochastic analysis with a focus on SDEs. He has also held visiting positions at the Mittag-Leffler Institute in Sweden and at several universities in Israel and Italy.
Boris Rozovsky earned his Master's degree in Probability and Statistics, followed by a PhD in Physical and Mathematical Sciences, both at Moscow State (Lomonosov) University. Having previously served as a Professor of Mathematics and Director of the Center for Applied Mathematical Sciences at the University of Southern California, he is currently the Ford Foundation Professor of Applied Mathematics at Brown University.

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