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Large Deviations For Stochastic Processes Hc.
592.80 EGP

Large Deviations For Stochastic Processes Hc.

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592.80 EGP 

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Category Type
General
ISBN
9780821841457
Author
Jin Feng
Publisher
American Mathematical Society
Description:

The book is devoted to the results on large deviations for a class of stochastic processes. Following an introduction and overview, the material is presented in three parts. Part 1 gives necessary and sufficient conditions for exponential tightness that are analogous to conditions for tightness in the theory of weak convergence. Part 2 focuses on Markov processes in metric spaces. For a ...

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    Specifications

    Category Type
    General
    ISBN
    9780821841457
    Item EAN
    2724546141833
    People
    Author
    Jin Feng
    People
    Publisher
    American Mathematical Society
    Category Type
    General
    ISBN
    9780821841457
    Item EAN
    2724546141833
    People
    Author
    Jin Feng
    People
    Publisher
    American Mathematical Society
    Technical Information
    Binding
    Paperback
    Languages and countries
    Book Language
    English
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  •  

    Description:

    The book is devoted to the results on large deviations for a class of stochastic processes. Following an introduction and overview, the material is presented in three parts. Part 1 gives necessary and sufficient conditions for exponential tightness that are analogous to conditions for tightness in

    The book is devoted to the results on large deviations for a class of stochastic processes. Following an introduction and overview, the material is presented in three parts. Part 1 gives necessary and sufficient conditions for exponential tightness that are analogous to conditions for tightness in the theory of weak convergence. Part 2 focuses on Markov processes in metric spaces. For a sequence of such processes, convergence of Fleming's logarithmically transformed nonlinear semigroups is shown to imply the large deviation principle in a manner analogous to the use of convergence of linear semigroups in weak convergence. Viscosity solution methods provide applicable conditions for the necessary convergence.Part 3 discusses methods for verifying the comparison principle for viscosity solutions and applies the general theory to obtain a variety of new and known results on large deviations for Markov processes. In examples concerning infinite dimensional state spaces, new comparison principles are derived for a class of Hamilton-Jacobi equations in Hilbert spaces and in spaces of probability measures.

    • Large Deviations For Stochastic Processes Hc.
    • Author: Jin Feng
    • Publisher: American Mathematical Society.
    • Published: 2006
 

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