Here is a matlab code to demonstrate the sampling theorem.
fig_size=[232 84 774 624];
Ts1=0.05;
Ts2=0.1;
Ts3=0.2;
ws1=2*pi/Ts1;
ws2=2*pi/Ts2;
ws3=2*pi/Ts3;
w1=7;
w2=23;
t=[0:0.005:2];
x=cos(w1*t)+cos(w2*t);
disp(‘X’);
disp(x);
subplot(2,3,1),plot(t,x),grid,xlabel(‘time(s)’),ylabel(‘amplitude’),….
title(‘continuous‐time signal; x(t)=cos(7t)+cos(23t)’),….
set(gcf,’position’,fig_size)
t1=[0:Ts1:2];
xs1=cos(w1*t1)+cos(w2*t1);
disp(‘xs1′);
disp(xs1);
subplot(2,3,2);
stem(t1,xs1);
grid,hold on,plot(t,x,’r'),hold off,….
xlabel(‘time(s)’),ylabel(‘amplitude’),….
title(‘sampled version of x(t) with Ts=0.05s’),….
set(gcf,’position’,fig_size)
t2=[0:Ts2:2];
xs2=cos(w1*t2)+cos(w2*t2);
subplot(2,3,3);
stem(t2,xs2);
grid,hold on,plot(t,x,’r'),hold off,….
xlabel(‘time(s)’),ylabel(‘amplitude’),….
title(‘sampled version of x(t) with Ts=0.1s’),….
set(gcf,’position’,fig_size)
t3=[0:Ts3:2];
xs3=cos(w1*t3)+cos(w2*t3);
subplot(2,3,4);
stem(t3,xs3);
grid,hold on,plot(t,x,’r'),hold off,….
xlabel(‘time(s)’),ylabel(‘amplitude’),….
title(‘sampled version of x(t) with Ts=0.2s’),….
set(gcf,’position’,fig_size)
w2s3=w2‐ws3;
x1=cos(w1*t)+cos(w2s3*t);
subplot(2,3,5);
stem(t3,xs3);
grid,hold on,plot(t,x,’k:’,t,x1,’r:’),hold off,….
xlabel(‘time(s)’),ylabel(‘amplitude’),….
title(‘sampled version of x(t) & x1(t) with Ts=0.2s’),….
set(gcf,’position’,fig_size)
text(1.13,1.2,’x(t)’),text(0.1,1.6,’x1(t)’)
n=[‐1 0 1];
wx=[‐w2 ‐w1 w1 w2];
wx1=[];
wx2=[];
wx3=[];
for i=1:length(n)
wx1=[wx1 (wx+n(i)*ws1)];
wx2=[wx2 (wx+n(i)*ws2)];
wx3=[wx3 (wx+n(i)*ws3)];
end
wx1=sort(wx1);
wx2=sort(wx2);
wx3=sort(wx3);
clear i
disp(wx1)
..