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In Lecture 13, we spent some more time discussing the relationship between the Fourier transform of a signal x(t) and the Fourier transform of its sampling y[n]=x(nT). (Note that it is VERY IMPORTANT that you understand this relationship.) We then introduced the concept of resampling.  
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In Lecture 13, we discussed the possibility of an extra credit project involving signal resampling and filtering.
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After this slight diversion, we continued discussing the sampling
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<math>x_1[n]=x(T_1 n)</math>
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of a continuous-time signal x(t). We obtained and discussed the relationship between the DT Fourier transform of <math>x_1[n]</math> and that of a downsampling <math>y[n]=x_1[Dn]</math>, for some integer D>1. We then obtained the relationship between the DT Fourier transform of  <math>x_1[n]</math> and that of an upsampling of x[n] by a factor D. In the next lecture, we will use this relationship to figure out how to transform this signal into the  (higher resolution) signal
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<math>x_2[n]=x\left( n \frac{T_1}{D} \right)</math>.
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Side notes:
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*I think this may be a good time to pass some advice to current/future ECE301 students on [[Peer_Legacy_ECE301|the peer legacy page]]. 
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*Here is a [[Student_summary_sampling_part1_ECE438F09|Rhea page on sampling contributed by a student]].
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*[[Hw3_ECE438F11|HW3]] is now posted. It is due next Wednesday.  
 
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<br> Previous: [[Lecture12ECE438F11|Lecture 12]] Next: [[Lecture14ECE438F11|Lecture 14]]  
 
<br> Previous: [[Lecture12ECE438F11|Lecture 12]] Next: [[Lecture14ECE438F11|Lecture 14]]  

Revision as of 12:12, 21 September 2011


Lecture 13 Blog, ECE438 Fall 2011, Prof. Boutin

Wednesday September 21, 2011 (Week 5) - See Course Outline.


In Lecture 13, we discussed the possibility of an extra credit project involving signal resampling and filtering.

After this slight diversion, we continued discussing the sampling

$ x_1[n]=x(T_1 n) $

of a continuous-time signal x(t). We obtained and discussed the relationship between the DT Fourier transform of $ x_1[n] $ and that of a downsampling $ y[n]=x_1[Dn] $, for some integer D>1. We then obtained the relationship between the DT Fourier transform of $ x_1[n] $ and that of an upsampling of x[n] by a factor D. In the next lecture, we will use this relationship to figure out how to transform this signal into the (higher resolution) signal

$ x_2[n]=x\left( n \frac{T_1}{D} \right) $.


Side notes:



Previous: Lecture 12 Next: Lecture 14


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