Power Spectral Density of Signal
Homework Answers
In the solution, we are using the fact that the Power Spectral
Density is the fourier transform of the autocorrelation function of
the random process. 
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Power Spectral Density of Signal
A signal s(t) can be expressed as the following equation: L-1...
2. (30 points) Let X(t) be a wide-sense stationary (WSS) random signal with power spectral density...
2. (30 points) Let X(t) be a wide-sense stationary (WSS) random signal with power spectral density S(f) = 1011(f/200), and let y(t) be a random process defined by Y(t) = 10 cos(2000nt + 1) where is a uniformly distributed random variable in the interval [ 027]. Assume that X(t) and Y(t) are independent. (a) Derive the mean and autocorrelation function of Y(t). Is Y(t) a WSS process? Why? (b) Define a random signal Z(t) = X(t)Y(t). Determine and sketch the...
Q.2 ICO2]10 Marks] The signal g(t) forms the input to the LPF circuit shown in the figure, where R l,and y(Dis the output. If the power spectral density (PSD) of the signal ge) is (a) The autoc...
Q.2 ICO2]10 Marks] The signal g(t) forms the input to the LPF circuit shown in the figure, where R l,and y(Dis the output. If the power spectral density (PSD) of the signal ge) is (a) The autocorrelation of g(t) (b) The 3-dB bandwidth of the LPF (c) The power of g(t) and y(t) (d) Based on your answers above, will it be better if the signal has more or less bandwith? (e) If a white noise of PSD No/2 is...
Find the power of the signal conponent of a P is the Fourice t of s,(0)(2.5 points) edf,where S.f density of pu nose (2.5 points) . Consider the RL circuit shown below. Assume that R-10 and L-IN....
Find the power of the signal conponent of a P is the Fourice t of s,(0)(2.5 points) edf,where S.f density of pu nose (2.5 points) . Consider the RL circuit shown below. Assume that R-10 and L-IN. Hint : Use Parseval's relationship if necessary i(t) e. What is the input signal-o-oise (SNR,ratio, defined as: SNR, 1olog..C)as polnts d. Find the output power spectral density of noise N,00 N,( HP, where HU) is the frequency response of the circuit, and N,(n)...
4. (8 points) A noise signal ni(t) with power spectrum density (PSD) S () = k...
4. (8 points) A noise signal ni(t) with power spectrum density (PSD) S () = k ) is applied at the input of an deal differentiator. Determine the PSD and the power of the output noise signal no(t) (hint: no(t) = 0).
A Random Telegraph Signal with rate λ > 0 is a random process X(t) (where for each t, X(t) ∈ {±1}) defined on [0,∞) with the following properties: X(0) = ±1 with probability 0.5 each, and X(t) switches between the two values ±1 at the points of arrival of
A Random Telegraph Signal with rate λ > 0 is a random process X(t) (where for
each t, X(t) ∈ {±1}) defined on [0,∞) with the following properties: X(0) = ±1
with probability 0.5 each, and X(t) switches between the two values ±1 at the
points of arrival of a Poisson process with rate λ i.e., the probability of k changes
in a time interval of length T isP(k sign changes in an interval of length T) = e
−λT...
Q.6 Determine the autocorrelation function and power spectral density of the random process olt)= m(t) cos(21f...
Q.6 Determine the autocorrelation function and power spectral density of the random process olt)= m(t) cos(21f t+), where m(t) is wide sense stationary random process, and is uniformly distributed over (0,2%) and independent of m(t).
3. (40 points) A binary communication system transmits signals s (0) (i = 1, 2). The...
3. (40 points) A binary communication system transmits signals s (0) (i = 1, 2). The receiver samples the received signal r(t) = s(t)+ n(t) at T and obtain the decision statistic r =r(T) = S(T) + n(T) = a, un, where the signal component is either a = + A or a, = -A with A >0 and n is the noise component. Assume that s (6) and s(l) are equally likely to be transmitted and the decision threshold...
random vibrations Problem 1 Two random variables x and y have the joint probability density function where c is a...
random vibrations
Problem 1 Two random variables x and y have the joint probability density function where c is a constant. Verify that x and y are statistically independent and find the value of c for plx, y) to be correctly normalized. Check that Elx) Elyl-0 and that Elx2] and Ely') are both infinite Problem 2. Each sample function x(t) of a random process x(t) is given by: where a, a2, wh, and w are constants but 61 and 62,...
Suppose the random variable X has probability density function (pdf) - { -1 < x<1 otherwise...
Suppose the random variable X has probability density function (pdf) - { -1 < x<1 otherwise C fx (x) C0 : where c is a constant. (a) Show that c = 1/7; (b) Graph fx (х); (c) Given that all of the moments exist, why are all the odd moments of X zero? (d) What is the median of the distribution of X? (e) Find E (X2) and hence var X; (f) Let X1, fx (x) What is the limiting...
Consider a sinusoidal signal with random phase, defined by x(t)=Acos(2πfct+θ), where A and FC are constant and θ is a random variable uniform distributed over interval [-π,π], that is f(θ)={█(1/2π,&-π≤θ≤π@0,&elsewhere)┤ Describe the autocorrelation RX(τ
Consider a sinusoidal signal with random phase, defined by , where A and FC are constant and is a random variable uniform distributed over interval [-, that isa) Describe the autocorrelation RX of a sinusoidal wave X(t)b) Describe the power spectral density SX of a sinusoidal wave X(t)Consider a sinusoidal signal with random phase, defined by , where A and FC are constant and is a random variable uniform distributed over interval [-, that isa) Describe the autocorrelation RX of...
2. (30 points) Let X(t) be a wide-sense stationary (WSS) random signal with power spectral density S(f) = 1011(f/200), and let y(t) be a random process defined by Y(t) = 10 cos(2000nt + 1) where is a uniformly distributed random variable in the interval [ 027]. Assume that X(t) and Y(t) are independent. (a) Derive the mean and autocorrelation function of Y(t). Is Y(t) a WSS process? Why? (b) Define a random signal Z(t) = X(t)Y(t). Determine and sketch the...
Q.2 ICO2]10 Marks] The signal g(t) forms the input to the LPF circuit shown in the figure, where R l,and y(Dis the output. If the power spectral density (PSD) of the signal ge) is (a) The autocorrelation of g(t) (b) The 3-dB bandwidth of the LPF (c) The power of g(t) and y(t) (d) Based on your answers above, will it be better if the signal has more or less bandwith? (e) If a white noise of PSD No/2 is...
Find the power of the signal conponent of a P is the Fourice t of s,(0)(2.5 points) edf,where S.f density of pu nose (2.5 points) . Consider the RL circuit shown below. Assume that R-10 and L-IN. Hint : Use Parseval's relationship if necessary i(t) e. What is the input signal-o-oise (SNR,ratio, defined as: SNR, 1olog..C)as polnts d. Find the output power spectral density of noise N,00 N,( HP, where HU) is the frequency response of the circuit, and N,(n)...
4. (8 points) A noise signal ni(t) with power spectrum density (PSD) S () = k ) is applied at the input of an deal differentiator. Determine the PSD and the power of the output noise signal no(t) (hint: no(t) = 0).
Q.6 Determine the autocorrelation function and power spectral density of the random process olt)= m(t) cos(21f t+), where m(t) is wide sense stationary random process, and is uniformly distributed over (0,2%) and independent of m(t).
3. (40 points) A binary communication system transmits signals s (0) (i = 1, 2). The receiver samples the received signal r(t) = s(t)+ n(t) at T and obtain the decision statistic r =r(T) = S(T) + n(T) = a, un, where the signal component is either a = + A or a, = -A with A >0 and n is the noise component. Assume that s (6) and s(l) are equally likely to be transmitted and the decision threshold...
random vibrations
Problem 1 Two random variables x and y have the joint probability density function where c is a constant. Verify that x and y are statistically independent and find the value of c for plx, y) to be correctly normalized. Check that Elx) Elyl-0 and that Elx2] and Ely') are both infinite Problem 2. Each sample function x(t) of a random process x(t) is given by: where a, a2, wh, and w are constants but 61 and 62,...
Suppose the random variable X has probability density function (pdf) - { -1 < x<1 otherwise C fx (x) C0 : where c is a constant. (a) Show that c = 1/7; (b) Graph fx (х); (c) Given that all of the moments exist, why are all the odd moments of X zero? (d) What is the median of the distribution of X? (e) Find E (X2) and hence var X; (f) Let X1, fx (x) What is the limiting...
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