Digital Signal Processing Homework Assignment #4

EE3660 Intro. to Digital Signal Processing
Homework Assignment #4: Chap. 7

I Paper Assignment (50%)
1. (10%) Determine DFS coefficients of the following periodic sequences:
(a) 𝑥𝑥�[𝑛𝑛] = 2 cos(𝜋𝜋𝜋𝜋/4)
(b) 𝑥𝑥�[𝑛𝑛] = 3 sin(0.25𝜋𝜋𝜋𝜋) + 4cos(0.75𝜋𝜋𝜋𝜋)
2. (10%) Let x[n] be an N-point sequence with an N-point DFT X[k].
(a) If N is even and if x[n] = −x[⟨𝑛𝑛 + 𝑁𝑁/2⟩𝑁𝑁] for all n, then show that X[k] = 0 for even k.
(b) Show that if N=4m where m is an integer and if x[n] = −x[⟨𝑛𝑛 + 𝑁𝑁/4⟩𝑁𝑁] for all n, then
X[k]=0 for k = 4l , 0 ≤ l ≤ 𝑁𝑁
4 − 1
3. (12%) Let 𝑥𝑥1[n],0 ≤ n ≤ 𝑁𝑁1 − 1, be an 𝑁𝑁1-point sequence and let 𝑥𝑥2[n], 0 ≤ n ≤ 𝑁𝑁2 − 1, be
an 𝑁𝑁2 -point sequence. Let 𝑥𝑥3[n] = 𝑥𝑥1[n] ∗ 𝑥𝑥2[n] and let 𝑥𝑥4[n] = 𝑥𝑥1[n]A○N 𝑥𝑥2[n] , N ≥
max(𝑁𝑁1, 𝑁𝑁2)
(a) Show that
𝑥𝑥4[n] = ∑ 𝑥𝑥3 ∞ [n + 𝑙𝑙N] 𝑙𝑙=−∞ (7.209)
(b) Let e[n] = 𝑥𝑥4[n] − 𝑥𝑥3[n], show that
e[n] = �
𝑥𝑥3[n + N], max(𝑁𝑁1, 𝑁𝑁2) ≤ 𝑁𝑁 < 𝐿𝐿
0, 𝑁𝑁 ≥ 𝐿𝐿
where L = 𝑁𝑁1 + 𝑁𝑁2 − 1
(c) Verify the results in (a) and (b) for 𝑥𝑥1 = {1𝑛𝑛=0, 2,3,4}, 𝑥𝑥2 = {4𝑛𝑛=0, 3,2,1}, and N=5 and N=8
4. (8%) Let 𝑥𝑥�[𝑛𝑛] be a periodic sequence with fundamental period N and let 𝑋𝑋�[𝑘𝑘] be its DFS. Let
𝑥𝑥�3[𝑛𝑛] be periodic with period 3N consisting of three periods of 𝑥𝑥�[𝑛𝑛] and let �𝑋𝑋3[𝑘𝑘] be its DFS.
Determine �𝑋𝑋3[𝑘𝑘] in terms of 𝑋𝑋�[𝑘𝑘].
5. (10%) The first five values of the 9-point DFT of a real-valued sequence x[n] are given by
{4, 2 − 𝑗𝑗3,3 + 𝑗𝑗2, −4 + 𝑗𝑗6,8 − 𝑗𝑗7}
Without computing IDFT and then DFT but using DFT properties only, determine the
DFT of each of the following sequences:
(a) 𝑥𝑥1[n] = x[⟨𝑛𝑛 + 2⟩9]
(b) 𝑥𝑥2[n] = 2x[⟨2 − 𝑛𝑛⟩9]
(c) 𝑥𝑥3[n] = x[n]A○9 x[⟨−𝑛𝑛⟩9]
(d) 𝑥𝑥4[n] = x2[𝑛𝑛]
(e) 𝑥𝑥5[n] = x[𝑛𝑛]e−j4πn/9
II Program Assignment (50%)
1. (8%) Let x[n] = n(0.9)𝑛𝑛𝑢𝑢[𝑛𝑛],
(a) Determine the DTFT 𝑋𝑋�(𝑒𝑒𝑗𝑗𝑗𝑗) of x[n]. Please write your calculations and answer on
your .mlx file.
(b) Choose first N = 20 samples of x[n] and compute the approximate DTFT 𝑋𝑋�𝑁𝑁(𝑒𝑒𝑗𝑗𝑗𝑗) using
the fft function. Plot magnitudes of 𝑋𝑋�(𝑒𝑒𝑗𝑗𝑗𝑗) and 𝑋𝑋�𝑁𝑁(𝑒𝑒𝑗𝑗𝑗𝑗) in one plot and compare your
results.
(c) Repeat part (b) using N = 50.
(d) Repeat part (b) using N = 100.
2. (10%)Let x[n] = 𝑥𝑥1[n] + 𝑗𝑗𝑥𝑥2[n] where sequences 𝑥𝑥1[n] and 𝑥𝑥2[n] are real-valued.
(a) Show that 𝑋𝑋1[k] = 𝑋𝑋𝑐𝑐𝑐𝑐𝑐𝑐[𝑘𝑘] 𝑎𝑎𝑎𝑎𝑎𝑎 𝑗𝑗𝑗𝑗2[k] = 𝑋𝑋𝑐𝑐𝑐𝑐𝑐𝑐[𝑘𝑘]. Please write your calculations and
answer on your .mlx file.
(b) Write a MATLAB function
[X1,X2] = tworealDFTs(x1,x2)
that implements the results in part (a).
(c) Verify your function on the following two sequences: 𝑥𝑥1[n] = 0.9𝑛𝑛, 𝑥𝑥2[n] = (1 − 0.8𝑛𝑛);
0 ≤ n ≤ 49
3. (9%) Let 𝑥𝑥1[n] = {1𝑛𝑛=0, 2,3,4,5} be a 5-point sequence and let 𝑥𝑥2[n] = {2𝑛𝑛=0, −1,1, −1} be a
4-point sequence.
(a) Determine 𝑥𝑥1[n]A○5 𝑥𝑥2[n] using hand calculations. Please write your calculations and 
answer on your .mlx file.
(b) Verify your calculations in (a) using the circonv function.
(c) Verify your calculations in (a) by computing the DFTs and IDFT.
4. (8%) Let 𝑥𝑥1[n] be an 𝑁𝑁1-point and 𝑥𝑥2[n] be an 𝑁𝑁2-point sequence. Let N ≥ max(N1,N2). Their
N-point circular convolution is shown to be equal to the aliased version of their linear convolution
in (7.209) in Program Assignment 3. This result can be used to compute the circular convolution
via the linear convolution.
(a) Develop a MATLAB function
y = lin2circonv(x,h)
that implements this approach.
(b) For x[n] = {1𝑛𝑛=0, 2,3,4} and h[n] = {1𝑛𝑛=0, −1,1, −1} determine their 4-point circular
convolution using the lin2circonv function and verify using the circonv function.
5. (15%) Let a 2D filter impulse response h[m, n] be given by
h[m,n] = �
1
2𝜋𝜋𝜎𝜎2 𝑒𝑒− 𝑚𝑚2+𝑛𝑛2
2𝜎𝜎2 , −128 ≤ m, n ≤ 127
0 , 𝑜𝑜𝑜𝑜ℎ𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒
where σ is a parameter. For this problem use the “Lena” image.
(a) For σ = 4, determine h[m, n] and compute its 2D-DFT H[k, l] via the fft2 function taking
care of shifting the origin of the array from the middle to the beginning (using the ifftshift
function). Show the log-magnitude of H[k, l] as an image.
(b) Process the “Lena” image in the frequency domain using the above H[k, l]. This will involve
taking 2D-DFT of the image, multiplying the two DFTs and then taking the inverse of the
product. Comment on the visual quality of the resulting filtered image.
(c) Repeat (a) and (b) for σ = 32 and comment on the resulting filtered image as well as the
difference between the two filtered images.
(d) The filtered image in part (c) also suffers from an additional distortion due to a spatialdomain aliasing effect in the circular convolution. To eliminate this artifact, consider both
the image and the filter h[m, n] as 512 × 512 size images using zero-padding in each
dimension. Now perform the frequency-domain filtering and comment on the resulting
filtered image.
(e) Repeat part (b) for σ = 4 but now using the frequency response 1 − H[k, l] for the filtering.
Compare the resulting filtered image with that in (b).