Matlab files

Here you can find some m-files with commentaries. To see the commentary, type

>> help filename

in Matlab command window. (here 'filename' should be replaced by actual name, for instance, euler).

Disclaimer: These files are provided "as is", without warranties of any kind.

Some fixed-stepsize Runge-Kutta type solvers for initial value problems:

Euler's method for scalar equations: euler1.m
Heun's method for scalar equations: heun1.m
The midpoint method for scalar equations: midpoint1.m
(General) Euler's method: euler.m
(General) Heun's method: heun.m
The (general) midpoint method: midpoint.m
Runge-Kutta method of order 4: rk4.m

One step at a time:

One step of Euler's method: eulerstep.m
One step of Heun's method: heunstep.m
One step of the midpoint method: midpointstep.m
One step of Runge-Kutta method of order 4: rk4step.m
A fixed-stepsize solver that can use any of the above as steps: solver1.m

Stability region:

Runge-Kutta method: plotrk.m

Some examples of modeling and simulation by IVPs:

Pendulum: pend.m
Two-body problem: orbit2.m
Solar system simulator: solar.m
Outer solar system data: outer.m

Variable step-size (aka adaptive) methods:

Runge-Kutta-Fehlberg order 4/order 5 embedded pair: rkf45.m

Implicit methods:

Backward Euler with Newton's method as a solver (fixed step-size): beuler.m

Equation solvers:

A simple implementation of Newton's method: newton.m
A simple implementation of the secant method: secant.m

Multistep methods:

Adams-Bashforth 4-step method: ab4.m
Adams-Bashforth / Adams-Moulton predictor-corrector pair of order 4: abm4.m

Shooting methods for 2nd order (Dirichlet) boundary value problems:

Linear shooting method (with fixed stepsize IVP solvers): linshoot.m
Shooting method using bisection (with fixed stepsize IVP solvers): bisectshoot.m
Shooting method using bisection (with Runge-Kutta-Fehlberg 4/5 variable stepsize solver): rkf45bisectshoot.m

Finite difference methods for 2nd order (Dirichlet) boundary value problems:

For linear problems: linfd.m
For nonlinear problems (using a fixed point iteration): fpifd.m
For nonlinear problems (using Newton's iteration): newtfd.m