Ulteriori informazioni
Klappentext Consists of papers given at the ICMS meeting held in 1994 on this topic, and brings together some of the world's best known authorities on stochastic partial differential equations. Zusammenfassung Stochastic partial differential equations can be used in many areas of science to model complex systems that evolve over time. Their analysis is currently an area of much research interest. This book consists of papers given at the ICMS meeting held in 1994 on this topic and it brings together some of the world's best known authorities on stochastic partial differential equations. Inhaltsverzeichnis 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....
