Malliavin Calculus with Applications to Stochastic Partial Differential Equations
eBook - PDF

Malliavin Calculus with Applications to Stochastic Partial Differential Equations

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Malliavin Calculus with Applications to Stochastic Partial Differential Equations

About this book

Malliavin calculus is a stochastic calculus of variations on the Wiener space. The main results of this theory are currently having influence on research developments at the cross section of probability and infinite-dimensional analysis. On the applied level, Malliavin calculus is used, for example, in the study by probabilistic methods of mathematical models in finance. This book presents some applications of Malliavin calculus to stochastic partial differential equations driven by Gaussian noises. The first five chapters are devoted to an introduction of the calculus itself, based on a general Gaussian space. In the last chapters of the book, recent research on regularity of the solution of stochastic partial differential equations, and the existence and smoothness of their probability laws, are discussed.

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Yes, you can access Malliavin Calculus with Applications to Stochastic Partial Differential Equations by Marta Sanz-Solé in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
EPFL PRESS
Year
2005
Print ISBN
9782940222063
eBook ISBN
9782889148684
Topic
Mathematics
Subtopic
Probability & Statistics
Index
Mathematics

Table of contents

  1. Introduction
  2. Contents
  3. 1 Integration by Parts and Absolute Continuity of Probability Laws
  4. 2 Finite Dimensional Malliavin Calculus
  5. 3 The Basic Operators of Malliavin Calculus
  6. 4 Representation of Wiener Functionals
  7. 5 Criteria for Absolute Continuity and Smoothness of Probability Laws
  8. 6 Stochastic Partial Differential Equations Driven by Spatially Homogeneous Gaussian Noise
  9. 7 Malliavin Regularity of Solutions of SPDE’s
  10. 8 Analysis of the Malliavin Matrix of Solutions of SPDE’s
  11. Definitions of spaces
  12. Bibliography
  13. Index