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1 pts Question 2 Your work with decrete me signal that has 10 samples, and discrete...
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Final Respondus LockDown Browser Webcam Que 1. ( 0) The ROC for this siis •> 0.5 . 0.5 < 1<2 Question 2 1 Su're working with discrete-time signal z[k]that has 10 samples, and discrete-time signal h[k]that has 5 samples. You want mpute the convolution of these two signals (i.e. 2[k] * h[k]) by taking the FFT of each signal, multiplying in the frequency ain, and then taking an IFFT. To do this, you must first zero-pad the signals...
ОО 0 1 0-1 Question 5 1 pts You're working with a discrete-time signal x[k]that has...
ОО 0 1 0-1 Question 5 1 pts You're working with a discrete-time signal x[k]that has 2029 samples. You'll use the FFT algorithm to compute samples of X(12) To do this, you'll pad the signal with zeros so the overall length of the padded signal is well-suited for the FFT algorithm. For the choices below, which padded signal length would be the best choice? (Note: The factorization of each number is also provided). Padded length: 2041 = 13. 157 Padded...
Can someone please help me with all these questions please? I desperately need it asap! Must be d...
Can someone please help me with all these
questions please? I desperately need it asap! Must be done with
MATLAB. Thumbs up will be guaranteed! Thank you so
much!!
A. Discrete Fourier Transform and zero padding For the signals x1[n] and x2[n] answer the following questions: x2 [n] = cos(2m30/100) + 0.5 cos(2nn40/100) 1) Compute and plot the length-N DFT magnitude of signals x1[n] and x2[n] with respect to frequency fr, where f and N is the number of samples....
Exercise 4. Computing and displaying the Fourier Transform of a signal Later in the semester it will become useful to d...
Exercise 4. Computing and displaying the Fourier Transform of a signal Later in the semester it will become useful to determine the frequency response of a signal or system by taking the Fourier Transform empirically (rather than computing it analytically). To do so we make use of the fft and fftshift commands. The fft command is an efficient implementation of the Discrete Fourier Transform (DFT) known as the Fast Fourier Transform (FFT). When the FFT is computed the samples are...
Discrete Time Signal Processing Question 1. Consider an IIR filter A(1-2-1 cos ω0) 1-2cos ω02-1+2...
Discrete Time Signal Processing Question 1. Consider an IIR filter A(1-2-1 cos ω0) 1-2cos ω02-1+2 I. Compute its impulse response using the difference equation with an impulse signal δ(n) as the input. Use trigonometric identities to simplify the result as much as you can 2. Draw the diagram showing the implementation of this filter in terms of adders, delays and multipliers Note: The IIR filter above generates a cosinusoidal signal when an impulse signal is applied at its input.] Question...
question 2 Question 2: (10 points) A narrowband signal has a bandwidth of 8 kHz centered on a carrier frequency of 150 kHz. It is proposed to represent this signal in discrete-time form by samplin...
question 2
Question 2: (10 points) A narrowband signal has a bandwidth of 8 kHz centered on a carrier frequency of 150 kHz. It is proposed to represent this signal in discrete-time form by sampling its in-phase and quadr ature components individually. What is the minimum sampling rate that can be used for this representation? tify you Jus answer. How would you reconstruct the original narrowband sig ampled versions of its in-phase and quadrature components?
Question 2: (10 points) A...
Discrete-Time Multiple Choice: Show your work for each question as much as you can (a) Which...
Discrete-Time Multiple Choice:
Show your work for each question as much as you can
(a) Which of the following systems is linear?) (B) y[n] 2 cos(x (n) (D) y[n] x(n) (b) Which of the following systems is time-invariant?() (C) yfn] n[n] (D) yIn] - x-2n] (B) y[n] - cos(nx(n)) (c) Which of the following systems is causal? () (A) yln]-2x[-n] (d) Which of the following systems is NOT stable? () (C) yln] vx(n) (B) yinl 50 sin(rIn)+ 10 cos(2x())D)h(n) (0.2)"u(r)...
Question 2: Consider the signal h[n] given by 11 n=0 h[n] = { -1 n=4 10...
Question 2: Consider the signal h[n] given by 11 n=0 h[n] = { -1 n=4 10 otherwise a) Calculate the z-transform H(z). Find its poles and zeros. b) Let H[k] be the 512-point DFT of h[n]. Show that H[0] = H[128] = H (256) = H[384] = 0 by substituting k = 0, 128, 256, 384 in the DFT formula 511 H[k] => b[m]e-jkan n=0 c) Now, show H[0] = H[128] = H (256] = H[384] = 0 directly using...
Question 6: We will consider a piece-wise constant 1D signal in this part. Assume the signal...
Question 6: We will consider a piece-wise constant 1D signal in this part. Assume the signal (a function f(t)) contains S = 10 discrete sub-intervals of equal length. Each sub-interval contains 50 samples. This signal is given below in the variable signal acquired at sample locations sampling_locations (also provided below). Plot the 1D signal, create one plot with the regular plot commands and one plot with the stem command (use subplots to plot the two next to each other in...
Can you please help me answer Task 2.b? Please show all work. fs=44100; no_pts=8192; t=([0:no_pts-1]')/fs; y1=sin(2...
Can you please help me answer Task 2.b?
Please show all work.
fs=44100; no_pts=8192;
t=([0:no_pts-1]')/fs;
y1=sin(2*pi*1000*t);
figure;
plot(t,y1);
xlabel('t (second)')
ylabel('y(t)')
axis([0,.004,-1.2,1.2]) % constrain axis so you can actually see
the wave
sound(y1,fs); % play sound using windows driver.
%%
% Check the frequency domain signal. fr is the frequency vector and
f1 is the magnitude of F{y1}.
fr=([0:no_pts-1]')/no_pts*fs; %in Hz
fr=fr(1:no_pts/2); % single-sided spectrum
f1=abs(fft(y1)); % compute fft
f1=f1(1:no_pts/2)/fs;
%%
% F is the continuous time Fourier. (See derivation...
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Final Respondus LockDown Browser Webcam Que 1. ( 0) The ROC for this siis •> 0.5 . 0.5 < 1<2 Question 2 1 Su're working with discrete-time signal z[k]that has 10 samples, and discrete-time signal h[k]that has 5 samples. You want mpute the convolution of these two signals (i.e. 2[k] * h[k]) by taking the FFT of each signal, multiplying in the frequency ain, and then taking an IFFT. To do this, you must first zero-pad the signals...
ОО 0 1 0-1 Question 5 1 pts You're working with a discrete-time signal x[k]that has 2029 samples. You'll use the FFT algorithm to compute samples of X(12) To do this, you'll pad the signal with zeros so the overall length of the padded signal is well-suited for the FFT algorithm. For the choices below, which padded signal length would be the best choice? (Note: The factorization of each number is also provided). Padded length: 2041 = 13. 157 Padded...
Can someone please help me with all these
questions please? I desperately need it asap! Must be done with
MATLAB. Thumbs up will be guaranteed! Thank you so
much!!
A. Discrete Fourier Transform and zero padding For the signals x1[n] and x2[n] answer the following questions: x2 [n] = cos(2m30/100) + 0.5 cos(2nn40/100) 1) Compute and plot the length-N DFT magnitude of signals x1[n] and x2[n] with respect to frequency fr, where f and N is the number of samples....
Exercise 4. Computing and displaying the Fourier Transform of a signal Later in the semester it will become useful to determine the frequency response of a signal or system by taking the Fourier Transform empirically (rather than computing it analytically). To do so we make use of the fft and fftshift commands. The fft command is an efficient implementation of the Discrete Fourier Transform (DFT) known as the Fast Fourier Transform (FFT). When the FFT is computed the samples are...
Discrete Time Signal Processing Question 1. Consider an IIR filter A(1-2-1 cos ω0) 1-2cos ω02-1+2 I. Compute its impulse response using the difference equation with an impulse signal δ(n) as the input. Use trigonometric identities to simplify the result as much as you can 2. Draw the diagram showing the implementation of this filter in terms of adders, delays and multipliers Note: The IIR filter above generates a cosinusoidal signal when an impulse signal is applied at its input.] Question...
question 2
Question 2: (10 points) A narrowband signal has a bandwidth of 8 kHz centered on a carrier frequency of 150 kHz. It is proposed to represent this signal in discrete-time form by sampling its in-phase and quadr ature components individually. What is the minimum sampling rate that can be used for this representation? tify you Jus answer. How would you reconstruct the original narrowband sig ampled versions of its in-phase and quadrature components?
Question 2: (10 points) A...
Discrete-Time Multiple Choice:
Show your work for each question as much as you can
(a) Which of the following systems is linear?) (B) y[n] 2 cos(x (n) (D) y[n] x(n) (b) Which of the following systems is time-invariant?() (C) yfn] n[n] (D) yIn] - x-2n] (B) y[n] - cos(nx(n)) (c) Which of the following systems is causal? () (A) yln]-2x[-n] (d) Which of the following systems is NOT stable? () (C) yln] vx(n) (B) yinl 50 sin(rIn)+ 10 cos(2x())D)h(n) (0.2)"u(r)...
Question 2: Consider the signal h[n] given by 11 n=0 h[n] = { -1 n=4 10 otherwise a) Calculate the z-transform H(z). Find its poles and zeros. b) Let H[k] be the 512-point DFT of h[n]. Show that H[0] = H[128] = H (256) = H[384] = 0 by substituting k = 0, 128, 256, 384 in the DFT formula 511 H[k] => b[m]e-jkan n=0 c) Now, show H[0] = H[128] = H (256] = H[384] = 0 directly using...
Question 6: We will consider a piece-wise constant 1D signal in this part. Assume the signal (a function f(t)) contains S = 10 discrete sub-intervals of equal length. Each sub-interval contains 50 samples. This signal is given below in the variable signal acquired at sample locations sampling_locations (also provided below). Plot the 1D signal, create one plot with the regular plot commands and one plot with the stem command (use subplots to plot the two next to each other in...
Can you please help me answer Task 2.b?
Please show all work.
fs=44100; no_pts=8192;
t=([0:no_pts-1]')/fs;
y1=sin(2*pi*1000*t);
figure;
plot(t,y1);
xlabel('t (second)')
ylabel('y(t)')
axis([0,.004,-1.2,1.2]) % constrain axis so you can actually see
the wave
sound(y1,fs); % play sound using windows driver.
%%
% Check the frequency domain signal. fr is the frequency vector and
f1 is the magnitude of F{y1}.
fr=([0:no_pts-1]')/no_pts*fs; %in Hz
fr=fr(1:no_pts/2); % single-sided spectrum
f1=abs(fft(y1)); % compute fft
f1=f1(1:no_pts/2)/fs;
%%
% F is the continuous time Fourier. (See derivation...
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