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Note: Suppose any suitable values that are not given to you. Given two time domain signals; x(t) and y(t) as follows: [-2.5V x(1) 2V 9 1 |t|≤ls otherwise y(t)=2.5V, 0 9 -28 ≤1≤0 0st≤2s otherwise (1) Generate and plot x(t) and y(t). (2) Generate and plot the autocorrelation function for each of x(1) and y(t). (3) Generate and plot the power spectral density for each of x(t) and y(t). (4) Generate and plot the cross correlation function. (5) Generate and plot the cross power spectral density. (6) Generate 2000 samples of a Gaussian noise, n(t), with mean value of 2 an variance of 4. (7) Plot the sample values of n(t) using two different ways. (8) Determine the actual mean, variance, and standard deviation. Comment on th results. (9) Determine the median, mode, and range. (10) Sketch the histogram assuming 15 intervals. (11) Generate and plot the probability density function (pdf) and its correspondin cumulative distribution function (cdf).

Note: Suppose any suitable values that are not given to you. Given two time domain signals; x(t) and y(t) as follows: [-2.5V x(1) 2V 9 1 |t|≤ls otherwise y(t)=2.5V, 0 9 -28 ≤1≤0 0st≤2s otherwise (1) Generate and plot x(t) and y(t). (2) Generate and plot the autocorrelation function for each of x(1) and y(t). (3) Generate and plot the power spectral density for each of x(t) and y(t). (4) Generate and plot the cross correlation function. (5) Generate and plot the cross power spectral density. (6) Generate 2000 samples of a Gaussian noise, n(t), with mean value of 2 an variance of 4. (7) Plot the sample values of n(t) using two different ways. (8) Determine the actual mean, variance, and standard deviation. Comment on th results. (9) Determine the median, mode, and range. (10) Sketch the histogram assuming 15 intervals. (11) Generate and plot the probability density function (pdf) and its correspondin cumulative distribution function (cdf).

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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Note: Suppose any suitable values that are not given to you. Given two time domain signals; x(t) and y(t) as follows: (-2.5V ={²² x(t)= |t|≤1s otherwise y(t) = 2.5V 0 " " -2s ≤t≤0 Ost≤2s otherwise (1) Generate and plot x(t) and y(t). (2) Generate and plot the autocorrelation function for each of x(1) and y(t). (3) Generate and plot the power spectral density for each of x(t) and y(t). (4) Generate and plot the cross correlation function. (5) Generate and plot the cross power spectral density. (6) Generate 2000 samples of a Gaussian noise, n(t), with mean value of 2 and variance of 4. (7) Plot the sample values of n(t) using two different ways. (8) Determine the actual mean, variance, and standard deviation. Comment on the results. (9) Determine the median, mode, and range. (10) Sketch the histogram assuming 15 intervals. (11) Generate and plot the probability density function (pdf) and its corresponding cumulative distribution function (cdf).
Transcribed Image Text:Note: Suppose any suitable values that are not given to you. Given two time domain signals; x(t) and y(t) as follows: (-2.5V ={²² x(t)= |t|≤1s otherwise y(t) = 2.5V 0 " " -2s ≤t≤0 Ost≤2s otherwise (1) Generate and plot x(t) and y(t). (2) Generate and plot the autocorrelation function for each of x(1) and y(t). (3) Generate and plot the power spectral density for each of x(t) and y(t). (4) Generate and plot the cross correlation function. (5) Generate and plot the cross power spectral density. (6) Generate 2000 samples of a Gaussian noise, n(t), with mean value of 2 and variance of 4. (7) Plot the sample values of n(t) using two different ways. (8) Determine the actual mean, variance, and standard deviation. Comment on the results. (9) Determine the median, mode, and range. (10) Sketch the histogram assuming 15 intervals. (11) Generate and plot the probability density function (pdf) and its corresponding cumulative distribution function (cdf).
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