Hi there.
Let's say I have mathematical model composed of several differential
equations, such as :
di/dt = cos(i)
dc/dt = alpha * (i(t) - c(t))
(sorry my maths are really bad, but I hope you get the point)
I would like to approximate the evolution of such a system iteratively. How
would you
I don't see anything in hackage off the top of my head. If it's a set
of DEs like that, Runge-Kutta is a good place to start if you want to
code your own integrator:
http://en.wikipedia.org/wiki/Runge-Kutta#The_classical_fourth-order_Runge.E2.80.93Kutta_method
But if it were me I would just use
On Tue, 25 Sep 2007, Thomas Girod wrote:
Let's say I have mathematical model composed of several differential
equations, such as :
di/dt = cos(i)
dc/dt = alpha * (i(t) - c(t))
(sorry my maths are really bad, but I hope you get the point)
I would like to approximate the evolution of such a
Here is a minimal answer using Yampa-like Signal Function and Arrow
notation. You have to load this using ghci -farrows.
import Control.Arrow
The differential equation you gave are indeed:
i = integral (cos i) + i0
c = integral (alpha * (i - c)) + c0
where i0 and c0 are the initial
