Chapter 4: Programming in Matlab - College of the Redwoods

Section 4.2 Control Structures in Matlab 321
However, a truly remarkable result occurs when we add the sinusoids in
Figure 4.9(a). This is easy to do because we saved each individual term in
a row of matrix A. Matlab’s sum command will sum the columns of matrix A,
effectively summing the first five terms of series (4.4) at each instant of time t.
figure
plot(t,sum(A))
We “tighten” the axes, add a grid, then annotate each axis. This produces
the image in Figure 4.9(b). Note the striking similarity to the square wave
in Figure 4.8.
axis tight
grid on
xlabel(’t-axis’)
ylabel(’y-axis’)
Figure 4.9.
(a)
Approximating a square wave with a Fourier series (5 terms).
(b)
Because we smartly stored the number of terms in the variable numterms,
to see the effect of adding the first 10 terms of the fourier series (4.4) is a simple
matter of changing numterms=5 to numterms=10 and running the program
again. The ouptut is shown in Figures 4.10(a) and (b). In Figure 4.10(b),
note the even closer resemblance to the square wave in Figure 4.8, except at the
ends, where the “ringing” exhibited there is known as Gibb’s Phenomenon. If you