(23 intermediate revisions by 3 users not shown)
Line 5: Line 5:
 
[[Category:signal processing]]   
 
[[Category:signal processing]]   
  
<center><font size= 10>
+
<center>
TITLE OF YOUR SLECTURE
+
<font size= 4>
 +
Topic 3:Fourier transform of "rep" and "comb"
 
</font size>
 
</font size>
  
A [https://www.projectrhea.org/learning/slectures.php slecture] by [[ECE]] student JOE BLO
+
A [https://www.projectrhea.org/learning/slectures.php slecture] by [[ECE]] student Youqin Liu
  
 
Partly based on the [[2014_Fall_ECE_438_Boutin|ECE438 Fall 2014 lecture]] material of [[user:mboutin|Prof. Mireille Boutin]].  
 
Partly based on the [[2014_Fall_ECE_438_Boutin|ECE438 Fall 2014 lecture]] material of [[user:mboutin|Prof. Mireille Boutin]].  
Line 15: Line 16:
 
----
 
----
 
----
 
----
ECE438 SELECTURE
 
  
+
==1.INTRODUCTION:==
<font size= 5>
+
The topic 3 is the Fourier Transform of the Comb and Rep function. In my selecture, I am going to introduce the definition, the Fourier Transformation and the relationship of Comb function and Rep function.
'''1.Introduction: In my selecture, I am going to introduce the definition, the Fourier Transformation and the relationship of Comb function and Rep function.
+
 
 +
==2.THEORY:==
 +
 
 +
(1)
 +
 
 +
[[Image:Combfunction3.jpg]]
 +
 
 +
Reference:https://engineering.purdue.edu/~bouman/ece637/notes/pdf/RepComb.pdf
 +
 
 +
 
 +
<font size= 4>According to the definition of the comb function: </font size>
  
2.THEORY:'''
 
</font size>
 
  
<font size= 3>(1)According to the definition of the comb function: </font size>
 
 
<math>comb_T\big(X(t)\big)= x(t)\cdot\ P_T(t)</math>  
 
<math>comb_T\big(X(t)\big)= x(t)\cdot\ P_T(t)</math>  
  
<font size= 3> where</font size> <math>P_T(t)= \sum_{n=-\infty}^\infty \delta(t-nT)</math>
 
  
<font size= 3>Do the Fourier Transform to the function:</font size>
+
<font size= 4> where</font size> <math>P_T(t)= \sum_{n=-\infty}^\infty \delta(t-nT)</math>
 +
 
 +
 
 +
<font size= 4>Do the Fourier Transform to the function:</font size>
 +
 
  
 
<math>F\bigg(comb_T\big(x(t)\big)\bigg) = F\big(x(t)\cdot P_T(t)\big)</math>
 
<math>F\bigg(comb_T\big(x(t)\big)\bigg) = F\big(x(t)\cdot P_T(t)\big)</math>
  
<font size= 3>
+
 
 +
<font size= 4>
 
According to the property of Fourier Transformation, the multiplication in the time domain is equal to the convolution in the frequency domain.</font size>
 
According to the property of Fourier Transformation, the multiplication in the time domain is equal to the convolution in the frequency domain.</font size>
  
Line 40: Line 51:
 
                   <math>=x(f)*F\big(P_T(t)\big)</math>
 
                   <math>=x(f)*F\big(P_T(t)\big)</math>
  
<font size= 3>Because </font size>  <math>P_T(t)= \sum_{n=-\infty}^\infty \delta(t-nT)</math>  <font size= 3> is a periodic function , so we can expand it to Fourier series. </font size>
+
<font size= 4>Because </font size>  <math>P_T(t)= \sum_{n=-\infty}^\infty \delta(t-nT)</math>  <font size= 4> is a periodic function , so we can expand it to Fourier series. </font size>
  
  
<math>P_T(t)\sum_{n=-\infty}^\infty F_n e^{jn\cdot 2\pi t/T} </math>
+
<math>P_T(t)=\sum_{n=-\infty}^\infty F_n e^{jn\cdot 2\pi t/T} </math>
  
  
Line 50: Line 61:
 
       <math>=\frac{1}{T}</math>
 
       <math>=\frac{1}{T}</math>
  
<font size= 3>So, </font size>  <math>P_T(t) = \frac{1}{T}\sum_{n=-\infty}^\infty F_n e^{jn\cdot 2\pi t/T} </math>
+
<font size= 4>So, </font size>  <math>P_T(t) = \frac{1}{T}\sum_{n=-\infty}^\infty F_n e^{jn\cdot 2\pi t/T} </math>
  
 
           <math>=\sum_{n=-\infty}^\infty \frac{1}{T} F(e^{jn\cdot 2\pi t/T}) </math>
 
           <math>=\sum_{n=-\infty}^\infty \frac{1}{T} F(e^{jn\cdot 2\pi t/T}) </math>
Line 58: Line 69:
 
           <math>= \frac{1}{T}P_{1/T}(f)</math>
 
           <math>= \frac{1}{T}P_{1/T}(f)</math>
  
<font size= 3>So, </font size>  <math>F\bigg(comb_T\big(x(t)\big)\bigg)=X(f)*\frac{1}{T}P_{1/T}(f)</math>
+
<font size= 4>So, </font size>  <math>F\bigg(comb_T\big(x(t)\big)\bigg)=X(f)*\frac{1}{T}P_{1/T}(f)</math>
  
 
                     <math>=\frac{1}{T}X(f)*P_{1/T}(f)</math>
 
                     <math>=\frac{1}{T}X(f)*P_{1/T}(f)</math>
Line 64: Line 75:
 
                     <math>=\frac{1}{T}rep_{1/T}X(f)</math>
 
                     <math>=\frac{1}{T}rep_{1/T}X(f)</math>
  
<font size= 3>(2)According to the definition of Rep function:</font size>
+
----
 +
<font size =4>(2)</font size>
  
<math>rep_T\big(x(t)\big):= x(t)*P_T(t)</math>
+
[[Image:Repfunction3.jpg]]
  
<math>=x(t)*\sum_{n=-\infty}^\infty \delta(t-nT)</math>
+
Reference:https://engineering.purdue.edu/~bouman/ece637/notes/pdf/RepComb.pdf
  
 +
<font size= 4>According to the definition of Rep function:</font size>
  
<font size= 3>So, </font size><math>F\bigg(rep_T\big(x(t)\big)\bigg)=F\bigg(x(t)*\sum_{n=-\infty}^\infty \delta(t-nT)\bigg)</math>
 
  
 +
        <math>rep_T\big(x(t)\big):= x(t)*P_T(t)</math>
  
<font size= 3>Use the impluse-train we get previously, according to the conclusion we get from Fourier Transformation of it, we know:</font size>
+
                    <math>=x(t)*\sum_{n=-\infty}^\infty \delta(t-nT)</math>
  
<math>F\big(P_T(t)\big)=\frac{1}{T}P_{1/T}(f)</math>
 
  
<font size= 3>So, </font size> <math>F\bigg(rep_T\big(x(t)\big)\bigg)=x(f)\cdot\frac{1}{T}P_{1/T}(f)</math>
+
<font size= 4>So, </font size><math>F\bigg(rep_T\big(x(t)\big)\bigg)=F\bigg(x(t)*\sum_{n=-\infty}^\infty \delta(t-nT)\bigg)</math>
  
  
<math>=\frac{1}{T}x(f)\cdot P_{1/T}(f)</math>
 
  
 +
<font size= 4>Use the impluse-train we get previously, according to the conclusion we get from Fourier Transformation of it, we know:</font size>
  
 +
          <math>F\big(P_T(t)\big)=\frac{1}{T}P_{1/T}(f)</math>
 +
 +
<font size= 4>So, </font size> <math>F\bigg(rep_T\big(x(t)\big)\bigg)=x(f)\cdot\frac{1}{T}P_{1/T}(f)</math>
 +
 +
                    <math>=\frac{1}{T}x(f)\cdot P_{1/T}(f)</math>
  
----
 
----
 
----
 
(create a question page and put a link below)
 
 
==[[slecture_title_of_slecture_review|Questions and comments]]==
 
==[[slecture_title_of_slecture_review|Questions and comments]]==
  
 
If you have any questions, comments, etc. please post them on [[slecture_title_of_slecture_review|this page]].
 
If you have any questions, comments, etc. please post them on [[slecture_title_of_slecture_review|this page]].
 
----
 
----
[[2014_Fall_ECE_438_Boutin|Back to ECE438, Fall 2014]]
+
[[2014_Fall_ECE_438_Boutin_digital_signal_processing_slectures|Back to ECE438 slectures, Fall 2014]]

Latest revision as of 18:55, 16 March 2015


Topic 3:Fourier transform of "rep" and "comb"

A slecture by ECE student Youqin Liu

Partly based on the ECE438 Fall 2014 lecture material of Prof. Mireille Boutin.



1.INTRODUCTION:

The topic 3 is the Fourier Transform of the Comb and Rep function. In my selecture, I am going to introduce the definition, the Fourier Transformation and the relationship of Comb function and Rep function.

2.THEORY:

(1)

Combfunction3.jpg

Reference:https://engineering.purdue.edu/~bouman/ece637/notes/pdf/RepComb.pdf


According to the definition of the comb function:


$ comb_T\big(X(t)\big)= x(t)\cdot\ P_T(t) $


where $ P_T(t)= \sum_{n=-\infty}^\infty \delta(t-nT) $


Do the Fourier Transform to the function:


$ F\bigg(comb_T\big(x(t)\big)\bigg) = F\big(x(t)\cdot P_T(t)\big) $


According to the property of Fourier Transformation, the multiplication in the time domain is equal to the convolution in the frequency domain.

$ F\bigg(comb_T\big(x(t)\big)\bigg) = F\big(x(t)\big)* F\big(P_T(t)\big) $

                 $ =x(f)*F\big(P_T(t)\big) $

Because $ P_T(t)= \sum_{n=-\infty}^\infty \delta(t-nT) $ is a periodic function , so we can expand it to Fourier series.


$ P_T(t)=\sum_{n=-\infty}^\infty F_n e^{jn\cdot 2\pi t/T}  $


$ \Rightarrow F_n = \frac{1}{T}\int\limits_{-T/2}^{T/2}P_T(t)e^{jn\cdot 2\pi t/T}dt $

      $ =\frac{1}{T} $

So, $ P_T(t) = \frac{1}{T}\sum_{n=-\infty}^\infty F_n e^{jn\cdot 2\pi t/T} $

         $ =\sum_{n=-\infty}^\infty \frac{1}{T} F(e^{jn\cdot 2\pi t/T})  $
         $ =\sum_{n=-\infty}^\infty \frac{1}{T} \delta(f-\frac{n}{T}) $
         $ = \frac{1}{T}P_{1/T}(f) $

So, $ F\bigg(comb_T\big(x(t)\big)\bigg)=X(f)*\frac{1}{T}P_{1/T}(f) $

                    $ =\frac{1}{T}X(f)*P_{1/T}(f) $
  
                    $ =\frac{1}{T}rep_{1/T}X(f) $

(2)

Repfunction3.jpg

Reference:https://engineering.purdue.edu/~bouman/ece637/notes/pdf/RepComb.pdf

According to the definition of Rep function:


        $ rep_T\big(x(t)\big):= x(t)*P_T(t) $
                   $ =x(t)*\sum_{n=-\infty}^\infty \delta(t-nT) $


So, $ F\bigg(rep_T\big(x(t)\big)\bigg)=F\bigg(x(t)*\sum_{n=-\infty}^\infty \delta(t-nT)\bigg) $


Use the impluse-train we get previously, according to the conclusion we get from Fourier Transformation of it, we know:

         $ F\big(P_T(t)\big)=\frac{1}{T}P_{1/T}(f) $

So, $ F\bigg(rep_T\big(x(t)\big)\bigg)=x(f)\cdot\frac{1}{T}P_{1/T}(f) $

                   $ =\frac{1}{T}x(f)\cdot P_{1/T}(f) $ 

Questions and comments

If you have any questions, comments, etc. please post them on this page.


Back to ECE438 slectures, Fall 2014

Alumni Liaison

Ph.D. 2007, working on developing cool imaging technologies for digital cameras, camera phones, and video surveillance cameras.

Buyue Zhang