MATLAB Mathematics - SERC - Index of

4 Function Functions
To try fminsearch, create a function three_var of three variables, x, y, and z.
function b = three_var(v)
x = v(1);
y = v(2);
z = v(3);
b = x.^2 + 2.5*sin(y) - z^2*x^2*y^2;
Now find a minimum for this function using x = -0.6, y = -1.2, and
z = 0.135 as the starting values.
v = [-0.6 -1.2 0.135];
a = fminsearch(@three_var,v)
a =
0.0000 -1.5708 0.1803
Fitting a Curve to Data
This section gives an example that shows how to fit an exponential function of
the form Ae – λt
to some data. The example uses the function fminsearch to
minimize the sum of squares of errors between the data and an exponential
function Ae – λt
for varying parameters A and λ. This section covers the
following topics.
• “Creating an M-file for the Example” on page 4-10
• “Running the Example” on page 4-11
• “Plotting the Results” on page 4-12
Creating an M-file for the Example
To run the example, first create an M-file that
• Accepts vectors corresponding to the x- and y-coordinates of the data
• Returns the parameters of the exponential function that best fits the data
To do so, copy and paste the following code into an M-file and save it as
fitcurvedemo in a directory on the MATLAB path.
function [estimates, model] = fitcurvedemo(xdata, ydata)
% Call fminsearch with a random starting point.
start_point = rand(1, 2);
4-10