Stochastic Partial Differential Equations

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  • Format: Paperback
  • Copyright: 1995-07-28
  • Publisher: Cambridge University Press
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Stochastic partial differential equations can be used in many areas of science to model complex systems evolving over time. This book assembles together some of the world's best known authorities on stochastic partial differential equations. Subjects include the stochastic Navier-Stokes equation, critical branching systems, population models, statistical dynamics, and ergodic properties of Markov semigroups. For all workers on stochastic partial differential equations, this book will have much to offer.

Table of Contents

1. Stochastic differential equations with boundary conditions and the change of measure method A. Alabert
2. The Martin boundary of the Brownian sheet O. Brockhaus
3. Neocompact sets and stochastic Navier-Stokes equations N. Cutland and J. Keisler
4. Numerical experiments with spdes J. Gaines
5. Contour processes of random trees J. Geiger
6. On a class of quasilinear stochastic differential equations of parabolic type: regular dependence of solutions on initial data N. Y. Goncharuk
7. Fluctuations of a two-level critical branching system L. Gorostiza
8. Non-persistence of two-level branching systems in low dimensions K. Hochberg and A. Wakolbing
9. The stochastic Wick-type Burger's equation H. Holden, T. Lindstrom and B. Oksendal
10. A weak interaction epidemic among diffusing particles I. Kaj
11. Noise and dynamic transitions G. Lythe
12. Backward stochastic differential equations and quasilinear partial differential equations X. Mao
13. Path integrals and finite dimensional filters S. Maybank
14. A skew product representation for the generator of a two sex population model J. Rebholz
15. A nonlinear hyperbolic spde: approximations and support C. Rovira and M. Sanz
16. Statistical dynamics with thermal noise R. Streater
17. Stochastic Hamilton-Jacobi equations A. Truma and H. Zhao
18. On backward filtering equations for SDE systems (direct approach) A. Y. Veretennikov
19. Ergodicity of Markov semigroups B. Zegarlinski.

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