Description

Book Synopsis
The main purpose of this book is to give a systematic treatment of the theory of stochastic differential equations and stochastic flow of diffeomorphisms, and through the former to study the properties of stochastic flows. The classical theory was initiated by K. Ità and since then has been much developed. Professor Kunita's approach here is to regard the stochastic differential equation as a dynamical system driven by a random vector field, including thereby ItÃ's theory as a special case. The book can be used with advanced courses on probability theory or for self-study. The author begins with a discussion of Markov processes, martingales and Brownian motion, followed by a review of ItÃ's stochastic analysis. The next chapter deals with continuous semimartingales with spatial parameters, in order to study stochastic flow, and a generalisation of Ito's equation. Stochastic flows and their relation with this are generalised and considered in chapter 4. It is shown that solutions of a g

Trade Review
"The book could be used with advanced courses on probability theory or for self study." MTW, JASA

Table of Contents
1. Stochastic processes and random fields; 2. Continuous semimartingales and stochastic integrals; 3. Semimartingales with spatial parameter and stochastic integrals; 4. Stochastic flows; 5. Convergence of stochastic flows; 6. Stochastic partial differential equations.

Stochastic Flows and Stochastic Differential Equations 24 Cambridge Studies in Advanced Mathematics Series Number 24

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    A Paperback by Hiroshi Kunita

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      Book details

      Publisher Cambridge University Press
      Published 4 March 1997
      ISBN-13 9780521599252
      978-0521599252
      ISBN-10 0521599253
      Also in:
      Differential calculus and equations Probability and statistics

      Description

      Book Synopsis
      The main purpose of this book is to give a systematic treatment of the theory of stochastic differential equations and stochastic flow of diffeomorphisms, and through the former to study the properties of stochastic flows. The classical theory was initiated by K. Ità and since then has been much developed. Professor Kunita's approach here is to regard the stochastic differential equation as a dynamical system driven by a random vector field, including thereby ItÃ's theory as a special case. The book can be used with advanced courses on probability theory or for self-study. The author begins with a discussion of Markov processes, martingales and Brownian motion, followed by a review of ItÃ's stochastic analysis. The next chapter deals with continuous semimartingales with spatial parameters, in order to study stochastic flow, and a generalisation of Ito's equation. Stochastic flows and their relation with this are generalised and considered in chapter 4. It is shown that solutions of a g

      Trade Review
      "The book could be used with advanced courses on probability theory or for self study." MTW, JASA

      Table of Contents
      1. Stochastic processes and random fields; 2. Continuous semimartingales and stochastic integrals; 3. Semimartingales with spatial parameter and stochastic integrals; 4. Stochastic flows; 5. Convergence of stochastic flows; 6. Stochastic partial differential equations.

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