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Stochastic Flows and Stochastic Differential Equations

Stochastic Flows and Stochastic Differential Equations

$92.99 (P)

Part of Cambridge Studies in Advanced Mathematics

  • Date Published: April 1997
  • availability: Available
  • format: Paperback
  • isbn: 9780521599252

$ 92.99 (P)

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About the Authors
  • Stochastic analysis and stochastic differential equations are rapidly developing fields in probability theory and its applications. This book provides a systematic treatment of stochastic differential equations and stochastic flow of diffeomorphisms and describes the properties of stochastic flows. Professor Kunita's approach regards the stochastic differential equation as a dynamical system driven by a random vector field, including K. Itô's classical theory. Beginning with a discussion of Markov processes, martingales and Brownian motion, Kunita reviews Itô's stochastic analysis. He places emphasis on establishing that the solution defines a flow of diffeomorphisms. This flow property is basic in the modern and comprehensive analysis of the solution and will be applied to solve the first and second order stochastic partial differential equations. This book will be valued by graduate students and researchers in probability. It can also be used as a textbook for advanced probability courses.

    • Excellent author
    • HB has sales in excess of 1000
    • Can be used for advanced courses or for self study
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    Reviews & endorsements

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

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    Product details

    • Date Published: April 1997
    • format: Paperback
    • isbn: 9780521599252
    • length: 364 pages
    • dimensions: 229 x 152 x 21 mm
    • weight: 0.53kg
    • availability: Available
  • 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.

  • Author

    Hiroshi Kunita, Kyushu University, Japan

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