SDE
Stochastic Differential Equations


SDE, a MATLAB library which illustrates the properties of stochastic differential equations and some algorithms for handling them, by Desmond Higham.

The original version of these routines is available at "http://www.maths.strath.ac.uk/~aas96106/algfiles.html".

Licensing:

The computer code and data files made available on this web page are distributed under the GNU LGPL license.

Languages:

SDE is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version.

Related Data and Programs:

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COLORED_NOISE, a MATLAB library which generates samples of noise obeying a 1/f^alpha power law.

CORRELATION, a MATLAB library which contains examples of statistical correlation functions.

ORNSTEIN_UHLENBECK, a MATLAB library which approximates solutions of the Ornstein-Uhlenbeck stochastic differential equation (SDE) using the Euler method and the Euler-Maruyama method.

PCE_BURGERS, a MATLAB program which defines and solves a version of the time-dependent viscous Burgers equation, with uncertain viscosity, using a polynomial chaos expansion in terms of Hermite polynomials, by Gianluca Iaccarino.

PCE_LEGENDRE, a MATLAB program which assembles the system matrix associated with a polynomal chaos expansion of a 2D stochastic PDE, using Legendre polynomials;

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sde_test

STOCHASTIC_DIFFUSION, MATLAB functions which implement several versions of a stochastic diffusivity coefficient.

STOCHASTIC_GRADIENT_ND_NOISE, a MATLAB program which solves an optimization problem involving a functional over a system with stochastic noise.

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Author:

Desmond Higham

Reference:

  1. Desmond Higham,
    An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations,
    SIAM Review,
    Volume 43, Number 3, September 2001, pages 525-546.

Source Code:


Last revised on 12 March 2019.