Course on rough paths : with an introduction to regularity structures / Peter K. Friz and Martin Hairer.
Material type:
- 9783319083315
- 519.2 23 F921
Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
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Books | ISI Library, Kolkata | 519.2 F921 (Browse shelf(Opens below)) | Available | 135844 |
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Includes bibliographical references and index.
1. Introduction --
2. The space of rough paths --
3. Brownian motion as a rough path --
4. Integration against rough paths --
5. Stochastic integration and Itô's formula --
6. Doob-Meyer type decomposition for rough paths --
7. Operations on controlled rough paths --
8. Solutions to rough differential equations --
9. Stochastic differential equations --
10. Gaussian rough paths --
11. Cameron-Martin regularity and applications --
12. Stochastic partial differential equations --
13. Introduction to regularity structures --
14. Operations on modelled distributions --
15. Application to the KPZ equation--
References--
Index.
This book presents the first thorough and easily accessible introduction to rough path analysis. When applied to stochastic systems, rough path analysis provides a means to construct a pathwise solution theory which, in many respects, behaves much like the theory of deterministic differential equations and provides a clean break between analytical and probabilistic arguments. It provides a toolbox allowing to recover many classical results without using specific probabilistic properties such as predictability or the martingale property. The study of stochastic PDEs has recently led to a significant extension - the theory of regularity structures - and the last parts of this book are devoted to a gentle introduction. Most of this course is written as an essentially self-contained textbook, with an emphasis on ideas and short arguments, rather than pushing for the strongest possible statements. A typical reader will have been exposed to upper undergraduate analysis courses and has some interest in stochastic analysis. For a large part of the text, little more than Itô integration against Brownian motion is required as background.
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