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= [[HW2_ECE301_Spring2011_Prof_Boutin|Homework 2]] Solutions, [[2011_Spring_ECE_301_Boutin|ECE301 Spring 2011 Prof. Boutin]] =
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= [[HW2 ECE301 Spring2011 Prof Boutin|Homework 2]] Solutions, [[2011 Spring ECE 301 Boutin|ECE301 Spring 2011 Prof. Boutin]] =
  
== Question 1 ==
+
== Question 1 ==
a)  
+
 
<math class = "inline">  
+
a) <math>  
 
E_\infty = \lim_{T \rightarrow \infty} \int_{-T}^{T} \left|e^{-t}u(t)\right|^2dt
 
E_\infty = \lim_{T \rightarrow \infty} \int_{-T}^{T} \left|e^{-t}u(t)\right|^2dt
 
= \lim_{T \rightarrow \infty} \int_{0}^{T} e^{-2t}dt
 
= \lim_{T \rightarrow \infty} \int_{0}^{T} e^{-2t}dt
= \lim_{T \rightarrow \infty} -\frac{1}{2}\left[e^{-2T}-e^0\right]=\frac{1}{2}
+
= \lim_{T \rightarrow \infty} -\frac{1}{2}\left[e^{-2T}-e^0\right]=\frac{1}{2}</math>  
</math>
+
  
 
+
<br> <math>  
<math class = "inline">  
+
 
P_\infty = \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{-T}^{T} \left|e^{-t}u(t)\right|^2dt
 
P_\infty = \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{-T}^{T} \left|e^{-t}u(t)\right|^2dt
 
= \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{0}^{T} e^{-2t}dt
 
= \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{0}^{T} e^{-2t}dt
 
= \lim_{T \rightarrow \infty} -\frac{1}{4T}\left[e^{-2T}-e^0\right]
 
= \lim_{T \rightarrow \infty} -\frac{1}{4T}\left[e^{-2T}-e^0\right]
= \lim_{T \rightarrow \infty} \frac{1-e^{-2T}}{4T}=0  
+
= \lim_{T \rightarrow \infty} \frac{1-e^{-2T}}{4T}=0 </math>  
</math>
+
 
+
  
Since the signal has '''finite energy''', then we expect that it has '''zero average power'''.<br><br>
+
<br> Since the signal has '''finite energy''', then we expect that it has '''zero average power'''.<br><br> b) <math>E_\infty = \lim_{T \rightarrow \infty} \int_{-T}^{T} \left|e^{jt}u(t)\right|^2dt
b)
+
<math class = "inline">
+
E_\infty = \lim_{T \rightarrow \infty} \int_{-T}^{T} \left|e^{jt}u(t)\right|^2dt
+
 
= \lim_{T \rightarrow \infty} \int_{0}^{T} dt
 
= \lim_{T \rightarrow \infty} \int_{0}^{T} dt
 
= \lim_{T \rightarrow \infty} T
 
= \lim_{T \rightarrow \infty} T
= \infty
+
= \infty</math><br><br> <math>P_\infty = \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{-T}^{T} \left|e^{jt}u(t)\right|^2dt
</math><br><br>
+
<math class = "inline">
+
P_\infty = \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{-T}^{T} \left|e^{jt}u(t)\right|^2dt
+
 
= \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{0}^{T} dt
 
= \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{0}^{T} dt
 
= \lim_{T \rightarrow \infty} \frac{T}{2T}
 
= \lim_{T \rightarrow \infty} \frac{T}{2T}
= \frac{1}{2}
+
= \frac{1}{2}</math>  
</math>
+
  
 
+
<br> Since the signal has '''infinite energy''', then we expect that it has '''average power that is greater than zero'''.<br><br> c) <math>E_\infty = \lim_{N \rightarrow \infty} \sum_{n=-N}^{N} \left|\frac{1}{3}u[n]\right|^2
Since the signal has '''infinite energy''', then we expect that it has '''average power that is greater than zero'''.<br><br>
+
c)
+
<math class = "inline">
+
E_\infty = \lim_{N \rightarrow \infty} \sum_{n=-N}^{N} \left|\frac{1}{3}u[n]\right|^2
+
 
= \lim_{N \rightarrow \infty} \sum_{n=0}^{N} \frac{1}{9}
 
= \lim_{N \rightarrow \infty} \sum_{n=0}^{N} \frac{1}{9}
 
= \lim_{N \rightarrow \infty} \frac{1}{9}(N+1)
 
= \lim_{N \rightarrow \infty} \frac{1}{9}(N+1)
= \infty
+
= \infty</math><br><br> <math>P_\infty = \lim_{N \rightarrow \infty} \frac{1}{2N+1}\sum_{n=-N}^{N} \left|\frac{1}{3}u[n]\right|^2
</math><br><br>
+
<math class = "inline">
+
P_\infty = \lim_{N \rightarrow \infty} \frac{1}{2N+1}\sum_{n=-N}^{N} \left|\frac{1}{3}u[n]\right|^2
+
 
= \lim_{N \rightarrow \infty} \frac{1}{2N+1} \sum_{n=0}^{N} \frac{1}{9}
 
= \lim_{N \rightarrow \infty} \frac{1}{2N+1} \sum_{n=0}^{N} \frac{1}{9}
 
= \lim_{N \rightarrow \infty} \frac{1}{9} \cdot \frac{N+1}{2N+1}
 
= \lim_{N \rightarrow \infty} \frac{1}{9} \cdot \frac{N+1}{2N+1}
 
= \frac{1}{9} \cdot \frac{1}{2}
 
= \frac{1}{9} \cdot \frac{1}{2}
= \frac{1}{18}
+
= \frac{1}{18}</math>  
</math>
+
  
 +
<br>
  
== Question 2 ==
+
== Question 2 ==
a)
+
<math class = "inline">
+
x[n+N] = e^{j\frac{3}{5}\pi(n+N-1/2)}
+
= e^{j\frac{3}{5}\pi N} \cdot e^{j\frac{3}{5}\pi(n-1/2)}
+
</math><br><br>
+
For <math>x[n+N]</math> to be equal to <math>x[n]</math>, <math class="inline">e^{j\frac{3}{5}\pi N}</math> should be equal to one.
+
  
 +
a) <math>x[n+N] = e^{j\frac{3}{5}\pi(n+N-1/2)}
 +
= e^{j\frac{3}{5}\pi N} \cdot e^{j\frac{3}{5}\pi(n-1/2)}</math><br><br> For <span class="texhtml">''x''[''n'' + ''N'']</span> to be equal to <span class="texhtml">''x''[''n'']</span>, <math>e^{j\frac{3}{5}\pi N}</math> should be equal to one.
  
This implies that <math class="inline">3\pi N/5 = 2\pi K</math>, where <math>k</math> is an integer, or <math> N=10k/3</math>. Now, the smallest positive integer N that is not zero is 10. Then the '''fundamental period of this signal is 10'''.
+
<br> This implies that <span class="texhtml">3π''N'' / 5 = 2π''K''</span>, where <span class="texhtml">''k''</span> is an integer, or <span class="texhtml">''N'' = 10''k'' / 3</span>. Now, the smallest positive integer N that is not zero is 10. Then the '''fundamental period of this signal is 10'''.  
  
 +
<br> b) <math>x(t)=\cos^2 t = \frac{1}{2}+\frac{1}{2}\cos(2t)</math><br> <math>x(t+T)= \frac{1}{2}+\frac{1}{2}\cos(2t+2T)</math><br> <span class="texhtml">''x''(''t'' + ''T'') = ''x''(''t'')</span> for <span class="texhtml">''T'' = π''k''</span>, where <span class="texhtml">''k''</span> is an integer. Now, the smallest positive nonzero <span class="texhtml">''T''</span> is <span class="texhtml">π</span>, and hence the '''fundamental period is '''<span class="texhtml">π</span>.
  
b)
+
<br> c) <math>x[n]=\cos^2 n = \frac{1}{2}+\frac{1}{2}\cos[2n]</math><br> <math>x[n+N]= \frac{1}{2}+\frac{1}{2}\cos[2n+2N]</math><br> <span class="texhtml">''x''[''n'' + ''N''] = ''x''[''n'']</span> for <span class="texhtml">''N'' = π''k''</span>, where <span class="texhtml">''k''</span> is an integer. Since <span class="texhtml">''x''[''n'']</span> is a discrete-time signal and <span class="texhtml">''N''</span> is a multiple of <span class="texhtml">π</span>, i.e. any non-zero <span class="texhtml">''N''</span> is not an interger, then we can say that the signal is '''not periodic'''.  
<math class ="inline">
+
x(t)=\cos^2 t = \frac{1}{2}+\frac{1}{2}\cos(2t)
+
</math><br>
+
<math class ="inline">
+
x(t+T)= \frac{1}{2}+\frac{1}{2}\cos(2t+2T)
+
</math><br>
+
<math>x(t+T)=x(t)</math> for <math>T=\pi k</math>, where <math>k</math> is an integer. Now, the smallest positive nonzero <math>T</math> is <math>\pi</math>, and hence the '''fundamental period is '''<math>\pi</math>.
+
  
 +
<br> d)<br> <math>\begin{align}
 +
x[n+N] &= 1 + e^{j\frac{4\pi}{7}(n+N)}-e^{j\frac{2\pi}{5}(n+N)} \\
 +
&= 1+e^{j\frac{4\pi}{7}N}\cdot e^{j\frac{4\pi}{7}n} - e^{j\frac{2\pi}{5}N} \cdot e^{j\frac{2\pi}{5} n} \\
 +
\end{align}</math>
  
c)
+
We can see that for <span class="texhtml">''N'' = 35''k''</span>, where k is an integer, <span class="texhtml">''x''[''n'' + ''N''] = ''x''[''n'']</span>. Then the '''fundamental frequency is 35'''.  
<math class ="inline">
+
x[n]=\cos^2 n = \frac{1}{2}+\frac{1}{2}\cos[2n]
+
</math><br>
+
<math class ="inline">
+
x[n+N]= \frac{1}{2}+\frac{1}{2}\cos[2n+2N]
+
</math><br>
+
<math>x[n+N]=x[n]</math> for <math>N=\pi k</math>, where <math>k</math> is an integer. Since <math>x[n]</math> is a discrete-time signal and <math>N</math> is a multiple of <math>\pi</math>, i.e. any non-zero <math>N</math> is not an interger, then we can say that the signal is '''not periodic'''.
+
  
 +
Note that we can find the fundamental frequency of this signal directly by knowing that the fundamental period of the sum of periodic signals is the least common multiple of the periods of the individual signals. For this specific signal, the first term has a fundamental period of 1, the second term has a fundamental period of 7, and the third term has a fundamental period of 5. Thus the fundamental period of the sum of these terms or signals is the least common multiple of 1, 7, and 5 which is 35. <br> Note also that the fundamental period of a complex exponential of the form <math>e^{j\frac{2\pi}{N}n}</math> is N.
  
d)<br>
+
e) If we let <math>f(t)=\frac{1}{1+t^2}</math>, then x(t) can be written in the form of <math>x(t) = \sum_{k=-\infty}^{\infty}f(t-7k)</math>.
<math class="inline">
+
\begin{align}
+
x[n+N] &= 1 + e^{j\frac{4\pi}{7}(n+N)}-e^{j\frac{2\pi}{5}(n+N)} \\
+
&= 1+e^{j\frac{4\pi}{7}N}\cdot e^{j\frac{4\pi}{7}n} - e^{j\frac{2\pi}{5}N} \cdot e^{j\frac{2\pi}{5} n} \\
+
\end{align}
+
</math>
+
  
We can see that for <math>N=35k</math>, where k is an integer, <math>x[n+N]=x[n]</math>. Then the '''fundamental frequency is 35'''.
+
Then the '''fundamental period is 7'''.  
  
Note that we can find the fundamental frequency of this signal directly by knowing that the fundamental period of the sum of periodic signals is the least common multiple of the periods of the individual signals. For this specific signal, the first term has a fundamental period of 1, the second term has a fundamental period of 7, and the third term has a fundamental period of 5. Thus the fundamental period of the sum of these terms or signals is the least common multiple of 1, 7, and 5 which is 35. <br>
+
<br>
Note also that the fundamental period of a complex exponential of the form <math class="inline">e^{j\frac{2\pi}{N}n}</math> is N.
+
<pre style="font-size: 1.25em; border: 1px solid black; padding: 6px;">How does the above show that the fundamental period is 7?  -mrgardne
 +
</pre>  
 +
<br>  
  
e) If we let <math class="inline">f(t)=\frac{1}{1+t^2}</math>, then x(t) can be written in the form of <math class="inline">x(t) = \sum_{k=-\infty}^{\infty}f(t-7k)</math>.
+
== Question 3  ==
  
Then the '''fundamental period is 7'''.
+
<math>x_e[n]=\frac{x[n]+x[-n]}{2}</math>
  
== Question 3 ==
+
<math>x_o[n]=\frac{x[n]-x[-n]}{2}</math>  
<math>x_e[n]=\frac{x[n]+x[-n]}{2}</math>
+
  
<math>x_o[n]=\frac{x[n]-x[-n]}{2}</math>
+
Now,
  
Now,
+
<math>\begin{align}
 
+
<math>
+
\begin{align}
+
 
\sum_{n=-\infty}^{\infty}x_e^2[n]+\sum_{n=-\infty}^{\infty}x_o^2[n] &= \sum_{n=-\infty}^{\infty}\left(x_e^2[n]+x_o^2[n]\right) \\
 
\sum_{n=-\infty}^{\infty}x_e^2[n]+\sum_{n=-\infty}^{\infty}x_o^2[n] &= \sum_{n=-\infty}^{\infty}\left(x_e^2[n]+x_o^2[n]\right) \\
 
&= \sum_{n=-\infty}^{\infty}\frac{x^2[n]+2x[n]x[-n]+x^2[-n] + x^2[n]-2x[n]x[-n]+x^2[-n]}{4} \\
 
&= \sum_{n=-\infty}^{\infty}\frac{x^2[n]+2x[n]x[-n]+x^2[-n] + x^2[n]-2x[n]x[-n]+x^2[-n]}{4} \\
Line 115: Line 77:
 
&= \frac{1}{2} \sum_{n=-\infty}^{\infty}x^2[n] + \frac{1}{2} \sum_{m=-\infty}^{\infty}x^2[m] \\
 
&= \frac{1}{2} \sum_{n=-\infty}^{\infty}x^2[n] + \frac{1}{2} \sum_{m=-\infty}^{\infty}x^2[m] \\
 
&= \sum_{n=-\infty}^{\infty}x^2[n].
 
&= \sum_{n=-\infty}^{\infty}x^2[n].
\end{align}
+
\end{align}</math>  
</math>
+
  
where we have used the change of variable m=-n.
+
where we have used the change of variable m=-n.  
  
== Question 4 ==
+
== Question 4 ==
We choose A440 as the single note that we will use to write out function <math>z(t)</math>.
+
  
Call this single note <math>a(t)</math>, then <math>a(t)=sin(2\pi f_At)[u(t)-u(t-1)]</math>, where <math>f_A=440</math> Hz.
+
We choose A440 as the single note that we will use to write out function <span class="texhtml">''z''(''t'')</span>.  
  
Here are the 12 notes of "Smoke on the Water" melody as a function of <math>a(t)</math> listed in order of time:
+
Call this single note <span class="texhtml">''a''(''t'')</span>, then <span class="texhtml">''a''(''t'') = ''s''''i''''n''(2π''f''<sub>''A''</sub>''t'')[''u''(''t'') − ''u''(''t'' − 1)]</span>, where <span class="texhtml">''f''<sub>''A''</sub> = 440</span> Hz.
  
<math>x_1(t)=a\left(2^{-\frac{1}{6}}t\right)\left[u(t)-u\left(t-\frac{60}{BPM}\right)\right]</math>
+
Here are the 12 notes of "Smoke on the Water" melody as a function of <span class="texhtml">''a''(''t'')</span> listed in order of time:
  
<math>x_2(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{60}{BPM}\right)\right]\left[u(t-\frac{60}{BPM})-u\left(t-\frac{120}{BPM}\right)\right]</math>
+
<math>x_1(t)=a\left(2^{-\frac{1}{6}}t\right)\left[u(t)-u\left(t-\frac{60}{BPM}\right)\right]</math>  
  
<math>x_3(t)=a\left[2^{\frac{1}{4}}\left(t-\frac{120}{BPM}\right)\right]\left[u(t-\frac{120}{BPM})-u\left(t-\frac{210}{BPM}\right)\right]</math>
+
<math>x_2(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{60}{BPM}\right)\right]\left[u(t-\frac{60}{BPM})-u\left(t-\frac{120}{BPM}\right)\right]</math>  
  
<math>x_4(t)=a\left[2^{-\frac{1}{6}}\left(t-\frac{210}{BPM}\right)\right]\left[u(t-\frac{210}{BPM})-u\left(t-\frac{270}{BPM}\right)\right]</math>
+
<math>x_3(t)=a\left[2^{\frac{1}{4}}\left(t-\frac{120}{BPM}\right)\right]\left[u(t-\frac{120}{BPM})-u\left(t-\frac{210}{BPM}\right)\right]</math>  
  
<math>x_5(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{270}{BPM}\right)\right]\left[u(t-\frac{270}{BPM})-u\left(t-\frac{330}{BPM}\right)\right]</math>
+
<math>x_4(t)=a\left[2^{-\frac{1}{6}}\left(t-\frac{210}{BPM}\right)\right]\left[u(t-\frac{210}{BPM})-u\left(t-\frac{270}{BPM}\right)\right]</math>  
  
<math>x_6(t)=a\left[2^{\frac{1}{3}}\left(t-\frac{330}{BPM}\right)\right]\left[u(t-\frac{330}{BPM})-u\left(t-\frac{360}{BPM}\right)\right]</math>
+
<math>x_5(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{270}{BPM}\right)\right]\left[u(t-\frac{270}{BPM})-u\left(t-\frac{330}{BPM}\right)\right]</math>  
  
<math>x_7(t)=a\left[2^{\frac{1}{4}}\left(t-\frac{360}{BPM}\right)\right]\left[u(t-\frac{360}{BPM})-u\left(t-\frac{480}{BPM}\right)\right]</math>
+
<math>x_6(t)=a\left[2^{\frac{1}{3}}\left(t-\frac{330}{BPM}\right)\right]\left[u(t-\frac{330}{BPM})-u\left(t-\frac{360}{BPM}\right)\right]</math>  
  
<math>x_8(t)=a\left[2^{\frac{-1}{6}}\left(t-\frac{480}{BPM}\right)\right]\left[u(t-\frac{480}{BPM})-u\left(t-\frac{540}{BPM}\right)\right]</math>
+
<math>x_7(t)=a\left[2^{\frac{1}{4}}\left(t-\frac{360}{BPM}\right)\right]\left[u(t-\frac{360}{BPM})-u\left(t-\frac{480}{BPM}\right)\right]</math>  
  
<math>x_9(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{540}{BPM}\right)\right]\left[u(t-\frac{540}{BPM})-u\left(t-\frac{600}{BPM}\right)\right]</math>
+
<math>x_8(t)=a\left[2^{\frac{-1}{6}}\left(t-\frac{480}{BPM}\right)\right]\left[u(t-\frac{480}{BPM})-u\left(t-\frac{540}{BPM}\right)\right]</math>  
  
<math>x_{10}(t)=a\left[2^{\frac{1}{4}}\left(t-\frac{600}{BPM}\right)\right]\left[u(t-\frac{600}{BPM})-u\left(t-\frac{690}{BPM}\right)\right]</math>
+
<math>x_9(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{540}{BPM}\right)\right]\left[u(t-\frac{540}{BPM})-u\left(t-\frac{600}{BPM}\right)\right]</math>  
  
<math>x_{11}(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{690}{BPM}\right)\right]\left[u(t-\frac{690}{BPM})-u\left(t-\frac{750}{BPM}\right)\right]</math>
+
<math>x_{10}(t)=a\left[2^{\frac{1}{4}}\left(t-\frac{600}{BPM}\right)\right]\left[u(t-\frac{600}{BPM})-u\left(t-\frac{690}{BPM}\right)\right]</math>  
  
<math>x_{12}(t)=a\left[2^{-\frac{1}{6}}\left(t-\frac{750}{BPM}\right)\right]\left[u(t-\frac{750}{BPM})-u\left(t-\frac{810}{BPM}\right)\right]</math>
+
<math>x_{11}(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{690}{BPM}\right)\right]\left[u(t-\frac{690}{BPM})-u\left(t-\frac{750}{BPM}\right)\right]</math>  
  
Finally, we can write <math>z(t)</math> as the sum of the above signals: <math class="inline">z(t)=x_1(t)+x_2(t)+\dots+x_{12}(t)</math>.
+
<math>x_{12}(t)=a\left[2^{-\frac{1}{6}}\left(t-\frac{750}{BPM}\right)\right]\left[u(t-\frac{750}{BPM})-u\left(t-\frac{810}{BPM}\right)\right]</math>  
  
== Question 5 ==
+
Finally, we can write <span class="texhtml">''z''(''t'')</span> as the sum of the above signals: <math>z(t)=x_1(t)+x_2(t)+\dots+x_{12}(t)</math>.
  
Denote the outputs of system 1 and system 2 by v(t) and z(t), respectively. Then, we have:
+
== Question 5  ==
  
<math>v(t)=x(3t+7)</math>,
+
Denote the outputs of system 1 and system 2 by v(t) and z(t), respectively. Then, we have:
  
<math>z(t)=v(5t-1)=x(3(5t-1)+7)=x(15t+4)</math>, and
+
<span class="texhtml">''v''(''t'') = ''x''(3''t'' + 7)</span>,  
  
<math>y(t)=z(-t)=x(15(-t)+4)=x(-15t+4)</math>.
+
<span class="texhtml">''z''(''t'') = ''v''(5''t'' − 1) = ''x''(3(5''t'' − 1) + 7) = ''x''(15''t'' + 4)</span>, and
  
Hence, the output of the cascade is <math>y(t)=x(-15t+4)</math>.
+
<span class="texhtml">''y''(''t'') = ''z''( − ''t'') = ''x''(15( − ''t'') + 4) = ''x''( − 15''t'' + 4)</span>.
 +
 
 +
Hence, the output of the cascade is <span class="texhtml">''y''(''t'') = ''x''( − 15''t'' + 4)</span>.  
  
 
----
 
----
[[HW2 ECE301 Spring2011 Prof Boutin|HW2]]
 
  
[[2011 Spring ECE 301 Boutin|Back to 2011 Spring ECE 301 Boutin]] <br>
+
[[HW2 ECE301 Spring2011 Prof Boutin|HW2]]
 +
 
 +
[[2011 Spring ECE 301 Boutin|Back to 2011 Spring ECE 301 Boutin]] <br>  
  
 
[[Category:2011_Spring_ECE_301_Boutin]]
 
[[Category:2011_Spring_ECE_301_Boutin]]

Revision as of 13:49, 15 February 2011

Homework 2 Solutions, ECE301 Spring 2011 Prof. Boutin

Question 1

a) $ E_\infty = \lim_{T \rightarrow \infty} \int_{-T}^{T} \left|e^{-t}u(t)\right|^2dt = \lim_{T \rightarrow \infty} \int_{0}^{T} e^{-2t}dt = \lim_{T \rightarrow \infty} -\frac{1}{2}\left[e^{-2T}-e^0\right]=\frac{1}{2} $


$ P_\infty = \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{-T}^{T} \left|e^{-t}u(t)\right|^2dt = \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{0}^{T} e^{-2t}dt = \lim_{T \rightarrow \infty} -\frac{1}{4T}\left[e^{-2T}-e^0\right] = \lim_{T \rightarrow \infty} \frac{1-e^{-2T}}{4T}=0 $


Since the signal has finite energy, then we expect that it has zero average power.

b) $ E_\infty = \lim_{T \rightarrow \infty} \int_{-T}^{T} \left|e^{jt}u(t)\right|^2dt = \lim_{T \rightarrow \infty} \int_{0}^{T} dt = \lim_{T \rightarrow \infty} T = \infty $

$ P_\infty = \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{-T}^{T} \left|e^{jt}u(t)\right|^2dt = \lim_{T \rightarrow \infty} \frac{1}{2T} \int_{0}^{T} dt = \lim_{T \rightarrow \infty} \frac{T}{2T} = \frac{1}{2} $


Since the signal has infinite energy, then we expect that it has average power that is greater than zero.

c) $ E_\infty = \lim_{N \rightarrow \infty} \sum_{n=-N}^{N} \left|\frac{1}{3}u[n]\right|^2 = \lim_{N \rightarrow \infty} \sum_{n=0}^{N} \frac{1}{9} = \lim_{N \rightarrow \infty} \frac{1}{9}(N+1) = \infty $

$ P_\infty = \lim_{N \rightarrow \infty} \frac{1}{2N+1}\sum_{n=-N}^{N} \left|\frac{1}{3}u[n]\right|^2 = \lim_{N \rightarrow \infty} \frac{1}{2N+1} \sum_{n=0}^{N} \frac{1}{9} = \lim_{N \rightarrow \infty} \frac{1}{9} \cdot \frac{N+1}{2N+1} = \frac{1}{9} \cdot \frac{1}{2} = \frac{1}{18} $


Question 2

a) $ x[n+N] = e^{j\frac{3}{5}\pi(n+N-1/2)} = e^{j\frac{3}{5}\pi N} \cdot e^{j\frac{3}{5}\pi(n-1/2)} $

For x[n + N] to be equal to x[n], $ e^{j\frac{3}{5}\pi N} $ should be equal to one.


This implies that N / 5 = 2πK, where k is an integer, or N = 10k / 3. Now, the smallest positive integer N that is not zero is 10. Then the fundamental period of this signal is 10.


b) $ x(t)=\cos^2 t = \frac{1}{2}+\frac{1}{2}\cos(2t) $
$ x(t+T)= \frac{1}{2}+\frac{1}{2}\cos(2t+2T) $
x(t + T) = x(t) for T = πk, where k is an integer. Now, the smallest positive nonzero T is π, and hence the fundamental period is π.


c) $ x[n]=\cos^2 n = \frac{1}{2}+\frac{1}{2}\cos[2n] $
$ x[n+N]= \frac{1}{2}+\frac{1}{2}\cos[2n+2N] $
x[n + N] = x[n] for N = πk, where k is an integer. Since x[n] is a discrete-time signal and N is a multiple of π, i.e. any non-zero N is not an interger, then we can say that the signal is not periodic.


d)
$ \begin{align} x[n+N] &= 1 + e^{j\frac{4\pi}{7}(n+N)}-e^{j\frac{2\pi}{5}(n+N)} \\ &= 1+e^{j\frac{4\pi}{7}N}\cdot e^{j\frac{4\pi}{7}n} - e^{j\frac{2\pi}{5}N} \cdot e^{j\frac{2\pi}{5} n} \\ \end{align} $

We can see that for N = 35k, where k is an integer, x[n + N] = x[n]. Then the fundamental frequency is 35.

Note that we can find the fundamental frequency of this signal directly by knowing that the fundamental period of the sum of periodic signals is the least common multiple of the periods of the individual signals. For this specific signal, the first term has a fundamental period of 1, the second term has a fundamental period of 7, and the third term has a fundamental period of 5. Thus the fundamental period of the sum of these terms or signals is the least common multiple of 1, 7, and 5 which is 35.
Note also that the fundamental period of a complex exponential of the form $ e^{j\frac{2\pi}{N}n} $ is N.

e) If we let $ f(t)=\frac{1}{1+t^2} $, then x(t) can be written in the form of $ x(t) = \sum_{k=-\infty}^{\infty}f(t-7k) $.

Then the fundamental period is 7.


How does the above show that the fundamental period is 7?  -mrgardne


Question 3

$ x_e[n]=\frac{x[n]+x[-n]}{2} $

$ x_o[n]=\frac{x[n]-x[-n]}{2} $

Now,

$ \begin{align} \sum_{n=-\infty}^{\infty}x_e^2[n]+\sum_{n=-\infty}^{\infty}x_o^2[n] &= \sum_{n=-\infty}^{\infty}\left(x_e^2[n]+x_o^2[n]\right) \\ &= \sum_{n=-\infty}^{\infty}\frac{x^2[n]+2x[n]x[-n]+x^2[-n] + x^2[n]-2x[n]x[-n]+x^2[-n]}{4} \\ &= \sum_{n=-\infty}^{\infty}\frac{x^2[n]+x^2[-n]}{2} \\ &= \frac{1}{2} \sum_{n=-\infty}^{\infty}x^2[n] + \frac{1}{2} \sum_{n=-\infty}^{\infty}x^2[-n] \\ &= \frac{1}{2} \sum_{n=-\infty}^{\infty}x^2[n] + \frac{1}{2} \sum_{m=-\infty}^{\infty}x^2[m] \\ &= \sum_{n=-\infty}^{\infty}x^2[n]. \end{align} $

where we have used the change of variable m=-n.

Question 4

We choose A440 as the single note that we will use to write out function z(t).

Call this single note a(t), then a(t) = s'i'n(2πfAt)[u(t) − u(t − 1)], where fA = 440 Hz.

Here are the 12 notes of "Smoke on the Water" melody as a function of a(t) listed in order of time:

$ x_1(t)=a\left(2^{-\frac{1}{6}}t\right)\left[u(t)-u\left(t-\frac{60}{BPM}\right)\right] $

$ x_2(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{60}{BPM}\right)\right]\left[u(t-\frac{60}{BPM})-u\left(t-\frac{120}{BPM}\right)\right] $

$ x_3(t)=a\left[2^{\frac{1}{4}}\left(t-\frac{120}{BPM}\right)\right]\left[u(t-\frac{120}{BPM})-u\left(t-\frac{210}{BPM}\right)\right] $

$ x_4(t)=a\left[2^{-\frac{1}{6}}\left(t-\frac{210}{BPM}\right)\right]\left[u(t-\frac{210}{BPM})-u\left(t-\frac{270}{BPM}\right)\right] $

$ x_5(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{270}{BPM}\right)\right]\left[u(t-\frac{270}{BPM})-u\left(t-\frac{330}{BPM}\right)\right] $

$ x_6(t)=a\left[2^{\frac{1}{3}}\left(t-\frac{330}{BPM}\right)\right]\left[u(t-\frac{330}{BPM})-u\left(t-\frac{360}{BPM}\right)\right] $

$ x_7(t)=a\left[2^{\frac{1}{4}}\left(t-\frac{360}{BPM}\right)\right]\left[u(t-\frac{360}{BPM})-u\left(t-\frac{480}{BPM}\right)\right] $

$ x_8(t)=a\left[2^{\frac{-1}{6}}\left(t-\frac{480}{BPM}\right)\right]\left[u(t-\frac{480}{BPM})-u\left(t-\frac{540}{BPM}\right)\right] $

$ x_9(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{540}{BPM}\right)\right]\left[u(t-\frac{540}{BPM})-u\left(t-\frac{600}{BPM}\right)\right] $

$ x_{10}(t)=a\left[2^{\frac{1}{4}}\left(t-\frac{600}{BPM}\right)\right]\left[u(t-\frac{600}{BPM})-u\left(t-\frac{690}{BPM}\right)\right] $

$ x_{11}(t)=a\left[2^{\frac{1}{12}}\left(t-\frac{690}{BPM}\right)\right]\left[u(t-\frac{690}{BPM})-u\left(t-\frac{750}{BPM}\right)\right] $

$ x_{12}(t)=a\left[2^{-\frac{1}{6}}\left(t-\frac{750}{BPM}\right)\right]\left[u(t-\frac{750}{BPM})-u\left(t-\frac{810}{BPM}\right)\right] $

Finally, we can write z(t) as the sum of the above signals: $ z(t)=x_1(t)+x_2(t)+\dots+x_{12}(t) $.

Question 5

Denote the outputs of system 1 and system 2 by v(t) and z(t), respectively. Then, we have:

v(t) = x(3t + 7),

z(t) = v(5t − 1) = x(3(5t − 1) + 7) = x(15t + 4), and

y(t) = z( − t) = x(15( − t) + 4) = x( − 15t + 4).

Hence, the output of the cascade is y(t) = x( − 15t + 4).


HW2

Back to 2011 Spring ECE 301 Boutin

Alumni Liaison

Recent Math PhD now doing a post-doctorate at UC Riverside.

Kuei-Nuan Lin