Description

Book Synopsis
01/07 This title is now available from Walter de Gruyter. Please see www.degruyter.com for more information. This book is devoted to stochastic operators in Hilbert space. A number of models in modern probability theory apply the notion of a stochastic operator in explicit or latent form. In this book, objects from the Gaussian case are considered. Therefore, it is useful to consider all random variables and elements as functionals from the Wiener process or its formal derivative, i.e. white noise. The book consists of five chapters. The first chapter is devoted to stochastic calculus and its main goal is to prepare the tools for solving stochastic equations. In the second chapter the structure of stochastic equations, mainly the structure of Gaussian strong linear operators, is studied. In chapter 3 the definition of the action of the stochastic operator on random elements in considered. Chapter 4 deals with the mathematical models in which the notions of stochastic calculus arise and in the final chapter the equation with random operators is considered.

Table of Contents
Frontmatter -- Contents -- Introduction -- Chapter 1. Stochastic calculus -- Chapter 2. Random maps in Hilbert space -- Chapter 3. The composition of random maps -- Chapter 4. Stochastic analysis and quantum mechanics -- Chapter 5. Equations with random operators -- Bibliography

Stochastic Analysis and Random Maps in Hilbert Space

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    A Hardback by A. A. Dorogovtsev


      View other formats and editions of Stochastic Analysis and Random Maps in Hilbert Space by A. A. Dorogovtsev

      Publisher: Brill
      Publication Date: 01/01/1994
      ISBN13: 9789067641630, 978-9067641630
      ISBN10:

      Description

      Book Synopsis
      01/07 This title is now available from Walter de Gruyter. Please see www.degruyter.com for more information. This book is devoted to stochastic operators in Hilbert space. A number of models in modern probability theory apply the notion of a stochastic operator in explicit or latent form. In this book, objects from the Gaussian case are considered. Therefore, it is useful to consider all random variables and elements as functionals from the Wiener process or its formal derivative, i.e. white noise. The book consists of five chapters. The first chapter is devoted to stochastic calculus and its main goal is to prepare the tools for solving stochastic equations. In the second chapter the structure of stochastic equations, mainly the structure of Gaussian strong linear operators, is studied. In chapter 3 the definition of the action of the stochastic operator on random elements in considered. Chapter 4 deals with the mathematical models in which the notions of stochastic calculus arise and in the final chapter the equation with random operators is considered.

      Table of Contents
      Frontmatter -- Contents -- Introduction -- Chapter 1. Stochastic calculus -- Chapter 2. Random maps in Hilbert space -- Chapter 3. The composition of random maps -- Chapter 4. Stochastic analysis and quantum mechanics -- Chapter 5. Equations with random operators -- Bibliography

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