ComPutATIONAL MATHEMATICS AND NUMERICAL ANALYSIS ANMC

Numerical Integration of Stochastic Differential Equations


Goals

In this course we will introduce and study numerical integrators for stochastic differential equations. These numerical methods are important for many applications.

 

Mean-square  (dark gray) and asymptotic stability region (dark and light grays) of the explicit Milstein–Talay method.

Sample of an SPDE modelling the electric potential in a neuron at fixed time (left), as a space-time function (right).


Teacher

Prof. Assyr Abdulle

Assistant

Timothée Pouchon will be present in his office, MA C2 615, on Thursday from 14:00 to 15:00 to answer your questions.

Organization of the course

Course: Monday from 11h15 to 13h00 at MA A3 31
Exercise session : Thursday from 10h15 to 12h00 at MA A3 31.

Exercises

Week
Series Week Series Week Series
Series 1
Series 2
Series 3
Series 4
Series 5
Series 6
Series 7
Series 8
Series 9
Series 10
Series 11
Series 12

Bibliography

L. Arnold, "Stochastic Differential Equations, Theory and applications".

L.C. Evans, "An Introduction to Stochastic Differential Equations", AMS, 2013.

A. Einstein, "Investigations on the theory of the Brownian Movement", Dover Publications, INC., 1956.

H-H. Kuo, "Introduction to Stochastic Integration", Springer, 2005.

P.E. Kloeden, E. Platen, "Numerical Solution of Stochastic Differential Equations", second edition, Springer, 1999.

G.N. Milstein, M.V. Tretyakov, "Stochastic Numerics for Mathematical Physics", Springer, 2004.

 

Pour les rappels sur les probabilités on peut consulter:

R. C. Dalang et D. Conus, "Introduction à la théorie des probabilités", 1ère édition, PPUR, 2014

R. Derrett, "Probability: Theory and Examples", Cambridge University Press 2010.

A. Gut, "Probability: A Graduate Course", 2nd édition, Springer, 2013.

Ch.E. Pfister, "Théorie des probabilités", première édition, PPUR, 2014.

Contacts

ANMC

EPFL-SB-MATH-ANMC
Station 8
CH-1015 Lausanne

Tél: +41 (0) 21 693 55 85
Fax: +41 (0) 21 693 58 39

 

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