Stochastic Numerics for Mathematical Physics
This book is a substantially revised and expanded edition reflecting major developments in stochastic numerics since the first edition was published in 2004. The new topics, in particular, include mean-square and weak approximations in the case of nonglobally Lipschitz coefficients of Stochastic Dif...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2021, 2021
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| Edition: | 2nd ed. 2021 |
| Series: | Scientific Computation
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Mean-square Approximation for Stochastic Differential Equations
- Weak Approximation for Stochastic Differential Equations: Foundations
- Weak Approximation for Stochastic Differential Equations: Special Cases
- Numerical Methods for SDEs with Small Noise
- Geometric Integrators and Computing Ergodic Limits