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[[Category:discrete Fourier transform]] | [[Category:discrete Fourier transform]] | ||
| − | = Practice | + | <center><font size= 4> |
| + | '''[[Digital_signal_processing_practice_problems_list|Practice Question on "Digital Signal Processing"]]''' | ||
| + | </font size> | ||
| + | |||
| + | Topic: Discrete Fourier Transform | ||
| + | |||
| + | (This problem clarifies how zero-padding a signal changes its DFT.) | ||
| + | </center> | ||
| + | ---- | ||
| + | ==Question== | ||
Compute the discrete Fourier transform of the discrete-time signal | Compute the discrete Fourier transform of the discrete-time signal | ||
| Line 38: | Line 47: | ||
I'll fix it tomorrow. Or someone can point out my error? | I'll fix it tomorrow. Or someone can point out my error? | ||
| − | :instructor's comment: There is a much easier way to answer this question. Take a close look at the formula for the DFT and try to use a "comparison" approach. -pm | + | :<span style="color:purple"> instructor's comment: There is a much easier way to answer this question. Take a close look at the formula for the DFT and try to use a "comparison" approach. -pm |
---- | ---- | ||
==Answer 2== | ==Answer 2== | ||
| − | <math>X_k = \sum_{n=0}^{N-1} x_n \cdot e^{-j 2 \pi \frac{k}{N} n} | + | <math>X_k = \sum_{n=0}^{N-1} x_n \cdot e^{-j 2 \pi \frac{k}{N} n} = \sum_{n=0}^{3} (-j)^n \cdot e^{-j 2 \pi \frac{k}{4} n} </math>. |
| + | |||
| + | <math>X_k = \sum_{n=0}^{3} e^{-j \pi \frac{n}{2}} e^{-j 2 \pi \frac{k}{4} {n}} </math>. | ||
| + | |||
| + | <math>X_k = \sum_{n=0}^{3} e^{-j \pi n \frac {1}{2} { (1 + k) } }</math>. | ||
| + | |||
| + | |||
| + | <math>X_k = \frac{1 - e^{-j \pi n \frac {1}{2} { (1 + k) } } \cdot n } {1 - e^{-j \pi n \frac {1}{2} { (1 + k) } }}</math>. | ||
| + | :<span style="color:purple"> Instructor's comment: This line looks suspicious, ,don't you think? On the left-hand-side, you have a function of k, on the right-hand-side, you have a function of k and n. Don't you think it must be wrong? -pm </span> | ||
| + | |||
| + | <math>X_k = 4</math>. | ||
| + | |||
| + | :<span style="color:purple"> Instructor's comment: How did you get from the previous line to here???? -pm </span> | ||
| + | |||
| + | ---- | ||
| + | ==Answer 3== | ||
| + | x[n] can be rewritten like this: | ||
| + | |||
| + | <math>x[n]=(-j)^{n} = (e^{-j\frac{\pi}{2}})^{n} = e^{-j\frac{\pi}{2}n} = e^{j\frac{3\pi}{2}n}</math> | ||
| + | |||
| + | And then it makes the problem pretty straight forward. | ||
| + | |||
| + | <math> | ||
| + | \begin{align} | ||
| + | X[k] &= \sum_{n=0}^{N-1} x[n] e^{\frac{-j 2 \pi k n}{N}} \\ | ||
| + | &=\sum_{n=0}^{3} e^{j \frac{3\pi}{2} n} e^{-j 2 \frac{\pi}{4} k n} \ \ \text{N=4 due to periodicity of signal}\\ | ||
| + | &=\sum_{n=0}^{3} e^{-j \frac{\pi}{2} n (k-3)} \\ | ||
| + | &= 4 \delta (k-3) \ \ \text{by comparison to IDFT formula} \\ | ||
| + | \end{align} | ||
| + | </math> | ||
---- | ---- | ||
[[2011_Fall_ECE_438_Boutin|Back to ECE438 Fall 2011 Prof. Boutin]] | [[2011_Fall_ECE_438_Boutin|Back to ECE438 Fall 2011 Prof. Boutin]] | ||
Latest revision as of 13:20, 21 April 2013
Practice Question on "Digital Signal Processing"
Topic: Discrete Fourier Transform
(This problem clarifies how zero-padding a signal changes its DFT.)
Question
Compute the discrete Fourier transform of the discrete-time signal
$ x[n]= (-j)^n $.
How does your answer related to the Fourier series coefficients of x[n]?
You will receive feedback from your instructor and TA directly on this page. Other students are welcome to comment/discuss/point out mistakes/ask questions too!
Answer 1
$ X_k = \sum_{n=0}^{N-1} x_n \cdot e^{-j 2 \pi \frac{k}{N} n} = \sum_{n=0}^{3} (-j)^n \cdot e^{-j 2 \pi \frac{k}{4} n} = 1 + (-j \cdot e^{-j \frac{\pi k}{2}} ) + (-1 \cdot e^{-j \frac{2\pi k}{2}} ) + (j \cdot e^{-j \frac{3\pi k}{2}} ) $
$ = 1 + (-j) \cdot (-j)^k + (-1) \cdot (1)^k + (j) \cdot (j)^k = (-j)^{k+1} + (j)^{k+1} = 0, -2, 0, 2 $
, when k = 0, 1 ,2 ,3. And it is periodic with K = 4.
Ouch... This is not right. since $ x[n] = (-j)^n = e^{((-j\pi/2) \cdot n )} $
it's fft should be only an impulse. And Matlab told me:
x = [1 -j -1 j];
fft(x)
ans =
0 0 0 4
I'll fix it tomorrow. Or someone can point out my error?
- instructor's comment: There is a much easier way to answer this question. Take a close look at the formula for the DFT and try to use a "comparison" approach. -pm
Answer 2
$ X_k = \sum_{n=0}^{N-1} x_n \cdot e^{-j 2 \pi \frac{k}{N} n} = \sum_{n=0}^{3} (-j)^n \cdot e^{-j 2 \pi \frac{k}{4} n} $.
$ X_k = \sum_{n=0}^{3} e^{-j \pi \frac{n}{2}} e^{-j 2 \pi \frac{k}{4} {n}} $.
$ X_k = \sum_{n=0}^{3} e^{-j \pi n \frac {1}{2} { (1 + k) } } $.
$ X_k = \frac{1 - e^{-j \pi n \frac {1}{2} { (1 + k) } } \cdot n } {1 - e^{-j \pi n \frac {1}{2} { (1 + k) } }} $.
- Instructor's comment: This line looks suspicious, ,don't you think? On the left-hand-side, you have a function of k, on the right-hand-side, you have a function of k and n. Don't you think it must be wrong? -pm
$ X_k = 4 $.
- Instructor's comment: How did you get from the previous line to here???? -pm
Answer 3
x[n] can be rewritten like this:
$ x[n]=(-j)^{n} = (e^{-j\frac{\pi}{2}})^{n} = e^{-j\frac{\pi}{2}n} = e^{j\frac{3\pi}{2}n} $
And then it makes the problem pretty straight forward.
$ \begin{align} X[k] &= \sum_{n=0}^{N-1} x[n] e^{\frac{-j 2 \pi k n}{N}} \\ &=\sum_{n=0}^{3} e^{j \frac{3\pi}{2} n} e^{-j 2 \frac{\pi}{4} k n} \ \ \text{N=4 due to periodicity of signal}\\ &=\sum_{n=0}^{3} e^{-j \frac{\pi}{2} n (k-3)} \\ &= 4 \delta (k-3) \ \ \text{by comparison to IDFT formula} \\ \end{align} $
