Markov Processes and Differential Equations Asymptotic Problems
Probabilistic methods can be applied very successfully to a number of asymptotic problems for second-order linear and non-linear partial differential equations. Due to the close connection between the second order differential operators with a non-negative characteristic form on the one hand and Mar...
| Main Author: | |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Basel
Birkhäuser Basel
1996, 1996
|
| Edition: | 1st ed. 1996 |
| Series: | Lectures in Mathematics. ETH Zürich
|
| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 1 Stochastic Processes Defined by ODE’s
- 2 Small Parameter in Higher Derivatives: Levinson’s Case
- 3 The Large Deviation Case
- 4 Averaging Principle for Stochastic Processes and for Partial Differential Equations
- 5 Averaging Principle: Continuation
- 6 Remarks and Generalizations
- 7 Diffusion Processes and PDE’s in Narrow Branching Tubes
- 8 Wave Fronts in Reaction-Diffusion Equations
- 9 Wave Fronts in Slowly Changing Media
- 10 Large Scale Approximation for Reaction-Diffusion Equations
- 11 Homogenization in PDE’s and in Stochastic Processes
- References