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#Example
 
#Example
 
#Conclusion
 
#Conclusion
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----
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----
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<font size = 2>
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== Introduction ==
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For real world application, higher sampling rates are preferred because reconstruction doesn't require filter to be as close to the ideal (sharper cutoff).
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This leads to the question, can you use
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<math> {x}_{1}[n] = x_{c}(n{T}_{1})</math>
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 +
to obtain
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<math>{x}_{u}[n] = {x}_{c}(n{T}_{u})</math>
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without having to fully reconstruct <math> {x}_{c}(t) </math>
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assume <math> {x}_{c}(t) </math> is a bandlimited CT signal,
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<math> {x}_{1}[n] </math> is a DT sampled signal of <math> {x}_{c}(t) </math> with sampling period <math> {T}_{1} </math>
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----
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----
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== Derivation ==
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Revision as of 14:16, 14 October 2014

Frequency Domain View of Upsampling

Why Interpolator needs a LPF after Upsampling


A slecture by ECE student Chloe Kauffman

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


Outline

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


Introduction

For real world application, higher sampling rates are preferred because reconstruction doesn't require filter to be as close to the ideal (sharper cutoff). This leads to the question, can you use

$ {x}_{1}[n] = x_{c}(n{T}_{1}) $

to obtain

$ {x}_{u}[n] = {x}_{c}(n{T}_{u}) $ without having to fully reconstruct $ {x}_{c}(t) $

assume $ {x}_{c}(t) $ is a bandlimited CT signal, $ {x}_{1}[n] $ is a DT sampled signal of $ {x}_{c}(t) $ with sampling period $ {T}_{1} $



Derivation


Alumni Liaison

Sees the importance of signal filtering in medical imaging

Dhruv Lamba, BSEE2010