
Ergodicity for Infinite Dimensional Systems
Cambridge University Press
Published on 16. May 1996
Book
Paperback/Softback
352 pages
978-0-521-57900-1 (ISBN)
Description
This book is devoted to the asymptotic properties of solutions of stochastic evolution equations in infinite dimensional spaces. It is divided into three parts: Markovian dynamical systems; invariant measures for stochastic evolution equations; invariant measures for specific models. The focus is on models of dynamical processes affected by white noise, which are described by partial differential equations such as the reaction-diffusion equations or Navier-Stokes equations. Besides existence and uniqueness questions, special attention is paid to the asymptotic behaviour of the solutions, to invariant measures and ergodicity. Some of the results found here are presented for the first time. For all whose research interests involve stochastic modelling, dynamical systems, or ergodic theory, this book will be an essential purchase.
Reviews / Votes
"In the reviewer's opinion, the monograph provides an important contribution to the theory of stochastic infinite-dimensional systems, especially to the investigation of their asymptotic behavior....Although the authors concentrate on their own results, they also have taken an important and successful step in this direction." Bohdan Maslowski, Mathematical ReviewsMore details
Series
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Product notice
Paperback (trade)
Illustrations
Worked examples or Exercises
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 21 mm
Weight
572 gr
ISBN-13
978-0-521-57900-1 (9780521579001)
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Schweitzer Classification
Other editions
Additional editions

G. Da Prato | J. Zabczyk
Ergodicity for Infinite Dimensional Systems
E-Book
03/2011
1st Edition
Cambridge University Press
€69.49
Available for download
Persons
Content
Part I. Markovian Dynamical Systems: 1. General dynamical systems; 2. Canonical Markovian systems; 3. Ergodic and mixing measures; 4. Regular Markovian systems; Part II. Invariant Measures For Stochastics For Evolution Equations: 5. Stochastic differential equations; 6. Existence of invariant measures; 7. Uniqueness of invariant measures; 8. Densities of invariant measures; Part III. Invariant Measures For Specific Models: 9. Ornstein-Uhlenbeck processes; 10. Stochastic delay systems; 11. Reaction-diffusion equations; 12. Spin systems; 13. Systems perturbed through the boundary; 14. Burgers equation; 15. Navier-Stokes equations; Appendices.