[2] Delay the signal by say 32 samples and reduce its amplitude by factor of say α = 0.7, call this xd(n) as shown below: xd(n) 5α n=34 N=25
[2] Delay the signal by say 32 samples and reduce its amplitude by factor of say α = 0.7, call this xd(n) as shown below: xd(n) 5α n=34 N=25
Introductory Circuit Analysis (13th Edition)
13th Edition
ISBN:9780133923605
Author:Robert L. Boylestad
Publisher:Robert L. Boylestad
Chapter1: Introduction
Section: Chapter Questions
Problem 1P: Visit your local library (at school or home) and describe the extent to which it provides literature...
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Question
i want to answer question 2
![[1]
[2]
[3]
[4]
[5]
[6]
Generate a single pulse for the transmitted signal as shown b
x(n)
5
0 n=4
Delay the signal by say 32 samples and reduce its amplitude by
factor of say a = 0.7, call this xd(n) as shown below:
xd(n)
5α
0
n=34
N=25
Generate N=256 samples of Gaussian random signal and call t
Generate the simulated received signal by adding the transmitt
and the noise signal w(n), i.e.
r(n) = ax(n-d) + sigman x w(n)
Where sigman is the noise amplitude (initially set this
using subplot(2,2,1), plot the signals x(n), xd(n), and r(n). A
and grid the each plot.
Estimate the cross-correlation sequence R.(m) and plot in
quadrant of the figure. Note, plot only half the samples of t
correlation sequence returned by the function xcorr. This ca
follows:
% Assuming there are N samples of x
Y=xcorr(r,x);
R=Y(1:N);
Rrx-fliplr(R);](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F58906621-8084-4d3f-8698-0a398061b942%2Fb93be77c-07e4-4f29-b4e5-734c855dddfe%2Fjnl04z8_processed.png&w=3840&q=75)
Transcribed Image Text:[1]
[2]
[3]
[4]
[5]
[6]
Generate a single pulse for the transmitted signal as shown b
x(n)
5
0 n=4
Delay the signal by say 32 samples and reduce its amplitude by
factor of say a = 0.7, call this xd(n) as shown below:
xd(n)
5α
0
n=34
N=25
Generate N=256 samples of Gaussian random signal and call t
Generate the simulated received signal by adding the transmitt
and the noise signal w(n), i.e.
r(n) = ax(n-d) + sigman x w(n)
Where sigman is the noise amplitude (initially set this
using subplot(2,2,1), plot the signals x(n), xd(n), and r(n). A
and grid the each plot.
Estimate the cross-correlation sequence R.(m) and plot in
quadrant of the figure. Note, plot only half the samples of t
correlation sequence returned by the function xcorr. This ca
follows:
% Assuming there are N samples of x
Y=xcorr(r,x);
R=Y(1:N);
Rrx-fliplr(R);
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