Numerical Solvers for SDEs
BrainPy
provides several numerical methods for stochastic differential equations (SDEs). Specifically, we provide explicit Runge-Kutta methods, derivative-free Milstein methods, and exponential Euler method for SDE numerical integration. For the introductionary tutorial for how to use BrainPy provided numerical solversfor SDEs, please see the document in Quickstart/Numerical Solvers.
[1]:
import brainpy as bp
bp.__version__
[1]:
'1.0.3'
Methods |
Keywords |
Ito SDE support |
Stratonovich SDE support |
Scalar Wiener support |
Vector Wiener support |
---|---|---|---|---|---|
srk1w1_scalar |
Yes |
Yes |
|||
srk2w1_scalar |
Yes |
Yes |
|||
KlPl_scalar |
Yes |
Yes |
|||
euler |
Yes |
Yes |
Yes |
Yes |
|
heun |
Yes |
Yes |
Yes |
||
milstein |
Yes |
Yes |
Yes |
Yes |
|
exponential_euler |
Yes |
Yes |
Yes |
Author:
Chaoming Wang
Email: adaduo@outlook.com
Date: 2021.05.29