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Stochastic Numerics for Mathematical Physics
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Mean-square approximation for stochastic differential equations
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Chapter 2
Weak approximation for stochastic differential equations
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Chapter 3
Numerical methods for SDEs with small noise
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Chapter 4
Stochastic Hamiltonian systems and Langevin-type equations
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Chapter 5
Simulation of space and space-time bounded diffusions
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Chapter 6
Random walks for linear boundary value problems
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Chapter 7
Probabilistic approach to numerical solution of the Cauchy problem for nonlinear parabolic equations
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Chapter 8
Numerical solution of the nonlinear Dirichlet and Neumann problems based on the probabilistic approach
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Chapter 9
Application of stochastic numerics to models with stochastic resonance and to Brownian ratchets
Overall attention for this book and its chapters
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Mentioned by
syllabi
1
institution with syllabi
Citations
dimensions_citation
441
Dimensions
Readers on
mendeley
42
Mendeley
Book overview
1. Mean-square approximation for stochastic differential equations
2. Weak approximation for stochastic differential equations
3. Numerical methods for SDEs with small noise
4. Stochastic Hamiltonian systems and Langevin-type equations
5. Simulation of space and space-time bounded diffusions
6. Random walks for linear boundary value problems
7. Probabilistic approach to numerical solution of the Cauchy problem for nonlinear parabolic equations
8. Numerical solution of the nonlinear Dirichlet and Neumann problems based on the probabilistic approach
9. Application of stochastic numerics to models with stochastic resonance and to Brownian ratchets
Summary
Syllabi
Dimensions citations
This data is correct as of December 2015 - for more up to date information, please visit
https://opensyllabus.org/
So far, Altmetric has seen this research output assigned in
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syllabus from an institution on Open Syllabus Project.
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