(New page: Assume a function <math>x(t)</math>. We wish to covert a signal sampled at <math>T_1</math> one sampled at <math>T_2</math> without having to reconstruct the original <math>x(t)</math> an...)
 
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2. <math>T_2</math> is a divider of <math>T_1</math>
 
2. <math>T_2</math> is a divider of <math>T_1</math>
  
To be continued...
+
In this discussion, we will look at the first case, ie. where <math>T_2</math> is a multiple of <math>T_1</math>.
 +
 
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Conversion can be accomplished by down-sampling <math>x_1[n]</math>
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 +
<math>x_1[n] \longrightarrow D = \frac{T_2}{T_1} \longrightarrow x_2[n]</math>
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<math>x_2[n] = x_1[Dn]</math>
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 +
where <math>D = \frac{T_2}{T_1}</math>
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 +
We observe that this is the same as doing <math>x_2[n] = x(T_2n)</math>
 +
 
 +
This in Fourier Domain becomes
 +
 
 +
<math>F(x_2[n]) = F(x_1[Dn])</math>
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 +
<math>X_2(\omega) = \sum_{n=-\infty}^{\infty} x_1[Dn] e^{-j \omega n}</math>
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 +
let <math>m = Dn</math>
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 +
<math>X_2(\omega) = \sum_{m=-\infty}^{\infty} x_1[m] e^{-j \omega \frac{m}{D}}</math>
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 +
where m is a multiple of D
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 +
Now, we can introduce a function <math>s_D[m]</math> such that
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<math>s_D[m] =
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 +
\begin{cases}
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  1,  & \mbox{if }m\mbox{ multiple of }D\\
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  0, & \mbox{else }
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\end{cases}
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 +
</math>
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 +
The Fourier series of this function can be represented as
 +
 
 +
<math>S_D[m] = \frac{1}{D} \sum_{k = 0}^{D-1} (e^{j \frac{2 \pi}{D} m})^k</math>
 +
 
 +
and therefore we get
 +
 
 +
<math>X_2(\omega) = \sum_{m = -\infty}^{\infty} S_D[m] e^{-j \omega \frac{m}{D}}</math>
 +
 
 +
<math>X_2(\omega) =  \sum_{m = -\infty}^{\infty} \frac{1}{D}\sum_{k = 0}^{D-1} e^{j k \frac{2 \pi}{D} m} x_1[m] e^{-j \omega \frac{m}{D}}</math>
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 +
<math>X_2(\omega) = \frac{1}{D} \sum_{k=0}^{D-1} \sum_{m=-\infty}^{\infty} x_1[m] e^{-j m (\frac{\omega - 2 \pi k}{D})}</math>
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 +
And since <math>\sum_{m=-\infty}^{\infty} x_1[m] e^{-j m (\frac{\omega - 2 \pi k}{D})} = X_1(\frac{\omega - 2 \pi k}{D})</math>
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 +
Therefore,
 +
<math>X_2(\omega) = \frac{1}{D} \sum_{k=0}^{D-1} X_1(\frac{\omega - 2 \pi k}{D})</math>

Revision as of 17:45, 22 September 2009

Assume a function $ x(t) $.

We wish to covert a signal sampled at $ T_1 $ one sampled at $ T_2 $ without having to reconstruct the original $ x(t) $ and then resampling at a new rate.

There are two cases here.

1. $ T_2 $ is a multiple of $ T_1 $

2. $ T_2 $ is a divider of $ T_1 $

In this discussion, we will look at the first case, ie. where $ T_2 $ is a multiple of $ T_1 $.

Conversion can be accomplished by down-sampling $ x_1[n] $

$ x_1[n] \longrightarrow D = \frac{T_2}{T_1} \longrightarrow x_2[n] $

$ x_2[n] = x_1[Dn] $

where $ D = \frac{T_2}{T_1} $

We observe that this is the same as doing $ x_2[n] = x(T_2n) $

This in Fourier Domain becomes

$ F(x_2[n]) = F(x_1[Dn]) $

$ X_2(\omega) = \sum_{n=-\infty}^{\infty} x_1[Dn] e^{-j \omega n} $

let $ m = Dn $

$ X_2(\omega) = \sum_{m=-\infty}^{\infty} x_1[m] e^{-j \omega \frac{m}{D}} $

where m is a multiple of D

Now, we can introduce a function $ s_D[m] $ such that

$ s_D[m] = \begin{cases} 1, & \mbox{if }m\mbox{ multiple of }D\\ 0, & \mbox{else } \end{cases} $

The Fourier series of this function can be represented as

$ S_D[m] = \frac{1}{D} \sum_{k = 0}^{D-1} (e^{j \frac{2 \pi}{D} m})^k $

and therefore we get

$ X_2(\omega) = \sum_{m = -\infty}^{\infty} S_D[m] e^{-j \omega \frac{m}{D}} $

$ X_2(\omega) = \sum_{m = -\infty}^{\infty} \frac{1}{D}\sum_{k = 0}^{D-1} e^{j k \frac{2 \pi}{D} m} x_1[m] e^{-j \omega \frac{m}{D}} $

$ X_2(\omega) = \frac{1}{D} \sum_{k=0}^{D-1} \sum_{m=-\infty}^{\infty} x_1[m] e^{-j m (\frac{\omega - 2 \pi k}{D})} $

And since $ \sum_{m=-\infty}^{\infty} x_1[m] e^{-j m (\frac{\omega - 2 \pi k}{D})} = X_1(\frac{\omega - 2 \pi k}{D}) $

Therefore, $ X_2(\omega) = \frac{1}{D} \sum_{k=0}^{D-1} X_1(\frac{\omega - 2 \pi k}{D}) $

Alumni Liaison

Abstract algebra continues the conceptual developments of linear algebra, on an even grander scale.

Dr. Paul Garrett