Cheg 258 - Lecture Notes - April 28, 2000
Announcements
Class notes
Scanned Notes
The main points of the lecture were
- Adaptive Step Size Algorithms
Goals:
After this class you should be able to:
- Write an integration algorithm which adapts the step size to the accuracy
of the integration process.
Reading
- The class notes and Ch. 8 of Kahaner.
Questions of the Day
- In the Fehlberg Runge-Kutta approach the two integration estimates have
global errors of O(h^4) and O(h^5). If the set tolerance is t, how do you calculate
the step size?
- How does this answer change if the equation is very stiff?
Matlab Example Codes
example 33
-
ode23.m
-
example 34
David.T.Leighton.1@nd.edu