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[1] Generate a single pulse for the transmitted signal as shown b x(n) 5 0n-4

[1] Generate a single pulse for the transmitted signal as shown b x(n) 5 0n-4

Introductory Circuit Analysis (13th Edition)
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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[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);
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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And question 5 this is the question complete

v) Using subplot(2,2,1), plot the signal x(n), xd(n) and r(n). Appropriately label and grid the each plot.
Transcribed Image Text:v) Using subplot(2,2,1), plot the signal x(n), xd(n) and r(n). Appropriately label and grid the each plot.
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And question 4 

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iv) Generate the simulate received signal by adding the transmitted signal x(n) 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 to 1).
Transcribed Image Text:iv) Generate the simulate received signal by adding the transmitted signal x(n) 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 to 1).
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And those ?

iii) Generate N=256 samples of Gaussian random signal and call this w(n). iv) Generate the simulate received signal by adding the transmitted signal x(n) 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 to 1).
Transcribed Image Text:iii) Generate N=256 samples of Gaussian random signal and call this w(n). iv) Generate the simulate received signal by adding the transmitted signal x(n) 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 to 1).
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