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...

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Bibliographic Details
Main Authors: Milstein, Grigori N., Tretyakov, Michael V. (Author)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2021, 2021
Edition:2nd ed. 2021
Series:Scientific Computation
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