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</pre>
 
</pre>
  
This code is wrong because the sampling frequency, Ts, is to large to get an accurate recreation of the
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It outputs:
signal. By Nyquist's theorem, the descrete sampling frequency must be twice the continuous frequency in order to avoid unwanted artifacts. In other words Ts=.5*T0.
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 +
[[Image: Ece301_Hw2B_messedUP.jpg _ECE301Fall2008mboutin| Original Plot]]
 +
 
 +
This code is wrong because the sampling frequency, Ts, is to large to produce an accurate recreation of the
 +
signal. I fixed this bug by reducing the sampling time by a factor of 20.
  
 
<pre>
 
<pre>
 
F0 = 13;
 
F0 = 13;
 
T0 = 1/F0;
 
T0 = 1/F0;
Ts = .5*T0;
+
Ts = .05*T0;
 
t  = 0:Ts:13*T0;
 
t  = 0:Ts:13*T0;
 
x  = real(exp(j*(2*pi*F0*t-pi/2)));
 
x  = real(exp(j*(2*pi*F0*t-pi/2)));
 
plot(t,x)
 
plot(t,x)
 
</pre>
 
</pre>
Explain what the bug is, and modify the above code to fix this bug. Post your answer on a Rhea page.
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 +
Now the output looks like this:
 +
 
 +
[[Image: Ece301_Hw2B.jpg _ECE301Fall2008mboutin| Fixed Plot]]

Latest revision as of 07:05, 10 September 2008

This is the original code:


F0 = 13;
T0 = 1/F0;
Ts = 0.07;
t  = 0:Ts:13*T0;
x  = real(exp(j*(2*pi*F0*t-pi/2)));
plot(t,x)

It outputs:

Original Plot

This code is wrong because the sampling frequency, Ts, is to large to produce an accurate recreation of the signal. I fixed this bug by reducing the sampling time by a factor of 20.

F0 = 13;
T0 = 1/F0;
Ts = .05*T0;
t  = 0:Ts:13*T0;
x  = real(exp(j*(2*pi*F0*t-pi/2)));
plot(t,x)

Now the output looks like this:

Fixed Plot

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