Stochastic Differential Equations and Applications
eBook - PDF

Stochastic Differential Equations and Applications

Volume 1

  1. 248 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Stochastic Differential Equations and Applications

Volume 1

About this book

Stochastic Differential Equations and Applications, Volume 1 covers the development of the basic theory of stochastic differential equation systems. This volume is divided into nine chapters. Chapters 1 to 5 deal with the basic theory of stochastic differential equations, including discussions of the Markov processes, Brownian motion, and the stochastic integral. Chapter 6 examines the connections between solutions of partial differential equations and stochastic differential equations, while Chapter 7 describes the Girsanov's formula that is useful in the stochastic control theory. Chapters 8 and 9 evaluate the behavior of sample paths of the solution of a stochastic differential system, as time increases to infinity. This book is intended primarily for undergraduate and graduate mathematics students.

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Yes, you can access Stochastic Differential Equations and Applications by Avner Friedman, Z. W. Birnbaum,E. Lukacs in PDF and/or ePUB format, as well as other popular books in Mathematics & Applied Mathematics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Academic Press
Year
2014
Print ISBN
9780122682018
eBook ISBN
9781483217871
Topic
Mathematics
Subtopic
Applied Mathematics
Index
Mathematics

Table of contents

  1. Front Cover
  2. Stochastic Differential Equations and Applications
  3. Copyright Page
  4. Table of Contents
  5. Preface
  6. General Notation
  7. Contents of Volume 2
  8. Chapter 1. Stochastic Processes
  9. Chapter 2. Markov Processes
  10. Chapter 3. Brownian Motion
  11. Chapter 4. The Stochastic Integral
  12. Chapter 5. Stochastic Differential Equations
  13. Chapter 6. Elliptic and Parabolic Partial Differential Equations and Their Relations to Stochastic Differential Equations
  14. Chapter 7. The Cameronā€“Martinā€“Girsanov Theorem
  15. Chapter 8. Asymptotic Estimates for Solutions
  16. Chapter 9. Recurrent and Transient Solutions
  17. References
  18. Index