(New page: = Lecture 15 Blog, ECE438 Fall 2010, Prof. Boutin = Monday September 28, 2010. ---- In Lecture #15, we obtained a "practical" formula for reconstructing the DTFT of a...) |
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| − | In Lecture #15, we | + | In Lecture #15, we recalled that, before computing the "DFT of discrete-time signal"(*see note below), one first needs to truncate the signal. Subsequently, one needs to repeat the resulting finite duration signal in order to create a periodic DT signal. The DFT of that periodic signal then corresponds to a sampling of the DTFT of the truncated signal. |
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| + | We discussed the artifacts created by signal truncation (leakage) and the problems created by sampling the DTFT (the "picket fence effect"). To illustrate the leakage effect, we [[DTFT_Window_Function|looked at the Fourier transform of a window function]]. | ||
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| − | + | *Note: Technically, the DFT is only defined for periodic signals. | |
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Previous: [[Lecture14ECE438F10|Lecture 14]]; Next: [[Lecture16ECE438F10|Lecture 16]] | Previous: [[Lecture14ECE438F10|Lecture 14]]; Next: [[Lecture16ECE438F10|Lecture 16]] | ||
Latest revision as of 15:57, 8 October 2010
Lecture 15 Blog, ECE438 Fall 2010, Prof. Boutin
Monday September 28, 2010.
In Lecture #15, we recalled that, before computing the "DFT of discrete-time signal"(*see note below), one first needs to truncate the signal. Subsequently, one needs to repeat the resulting finite duration signal in order to create a periodic DT signal. The DFT of that periodic signal then corresponds to a sampling of the DTFT of the truncated signal.
We discussed the artifacts created by signal truncation (leakage) and the problems created by sampling the DTFT (the "picket fence effect"). To illustrate the leakage effect, we looked at the Fourier transform of a window function.
- Note: Technically, the DFT is only defined for periodic signals.
Previous: Lecture 14; Next: Lecture 16
