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==Introduction==
 
==Introduction==
  
  <math> X(f) </math> (the CTFT of <math> x(t) </math>  ),  <math> X_s(f) </math> (the CTFT of <math> x_s(t) </math> )  <math> X_d(\omega) </math> (the DTFT of <math> x_d[n] </math> )
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  This slecture covers definition of downsampling and demonstrates how to obtain downsampled signal in frequency domain.
 
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Revision as of 11:18, 9 October 2014


Frequency domain view of the relationship between a signal and a sampling of that signal

A slecture by ECE student Yerkebulan Yeshmukhanbetov

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


Outline

  1. Introduction
  2. Derivation
  3. Example
  4. Conclusion

Introduction

This slecture covers definition of downsampling and demonstrates how to obtain downsampled signal in frequency domain.

Derivation

signal: $  x_s(t)  $ and $  x_d[n]  $. $  x_s(t)  $   $  P_T(t)  $ with the original signal $  x(t)  $ and actually $  x_s(t)  $  is  $  comb_T(x(t))  $ where T is the sampling period.

However the $ x_d[n] $ is $ x(nT) $ where T is the sampling period.

relationship between $  X(f)  $ and $  X_s(f)  $. 

We know that $ x_s(t) = x(t) \times P_T(t) $, we can derive the relationship between $ x_s(t) $ and $ x(t) $ in the following way:

$ \begin{align} F(comb_T(x(t)) &= F(x(t) \times P_T(t))\\ &= X(f)*F(P_T(t))\\ &= X(f)*\frac{1}{T}\sum_{n = -\infty}^\infty \delta(f-\frac{n}{T})\\ &= \frac{1}{T}X(f)*P_\frac{1}{T}(f)\\ &= \frac{1}{T}rep_\frac{1}{T}X(f)\\ \end{align} $

Show this relationship in graph below:


example

Xfcbt.png

Xsfcbt.png


Derivation

n $ X_s(f) $ and $ X_d(\omega) $

We know another way to express CTFT of $ x_s(t) $:

$ \begin{align} X_s(f) &= F(\sum_{n = -\infty}^\infty x(nT)\delta(t-nT))\\ &= \sum_{n = -\infty}^\infty x(nT)F(\delta(t-nT))\\ &= \sum_{n = -\infty}^\infty x(nT)e^{-j2\pi fnT}\\ \end{align} $

compare it with DTFT of $ x_d[n] $:

$ \begin{align} X_d(\omega) &= \sum_{n = -\infty}^\infty x_d[n]e^{-j\omega n}\\ &= \sum_{n = -\infty}^\infty x(nT)e^{-j\omega n}\\ \end{align} $

we can find that:

$ \begin{align} X_d(2\pi Tf) &= X_s(f)\\ \end{align} $

if $ f = \frac{1}{T} $

we have that:

$ \begin{align} X_d(2\pi ) &= X_s(\frac{1}{T})\\ \end{align} $

ationship between $ X_s(f) $ and $ X_d(\omega) $ and the is showed in graph as below:


example

Xsfcbt.png

Xdwcbt.png


conclusion

So the relationship between $ X(f) $ and $ X_s(f) $ is that $ X_s(f) $ is a a rep of $ X(f) $ in frequency domain with period of $ \frac{1}{T} $ and magnitude scaled by $ \frac{1}{T} $. the relationship between $ X(f) $ and $ X_d(\omega) $ is that $ X_d(\omega) $ is also a a rep of $ X(f) $ in frequency domain with period $ 2\pi $ and magnitude is also scaled by $ \frac{1}{T} $, but the frequency is scaled by $ 2\pi T $


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