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2. The following causal system is excited by white noise (x[n)=w(n)) of zero mean and unit...
The following causal system is excited by white noise (x(n)=w(n)) of zero mean and unit variance....
The following causal system is excited by white noise (x(n)=w(n)) of zero mean and unit variance. The output is y(n). q(n)=x(n) - 0.8 q(n-1) y(n)=0.2 q(n) a) Determine the autocorrelation of the output y(n) in closed form for all m. Give numerical values for ryy(0), ryy(1), ryy(2). b) Find the variance of y(n). Give a numerical value and show all your work. c) Find the poles and zeros of the power spectral density (PSD) of y(n) and sketch them carefully...
A causal filter H(z) is excited by x(n) which is a white noise signal of zero...
A causal filter H(z) is excited by x(n) which is a white noise signal of zero mean 2 and unit variance. Its output is y(n). (28 points) H(2)05 Z-0.9 Give the autocorrelation of y(n) in closed form. Show all your work Give numerical values for ryy(0).1(1).1(2) a. b. Give the variance of y(n). c. Give the power spectral density (PSD) of y(n). d.
A causal filter H(z) is excited by x(n) which is a white noise signal of zero mean...
Q1) Let X(t) be a zero-mean WSS process with X(t) is input to an LTI system with Let Y(t) be the output. a) Find the mean of Y(t) b) Find the PSD of the output SY(f) c) Find RY(0) -----------------...
Q1) Let X(t) be a zero-mean WSS process with X(t) is input to an LTI system with Let Y(t) be the output. a) Find the mean of Y(t) b) Find the PSD of the output SY(f) c) Find RY(0) ------------------------------------------------------------------------------------------------------------------------- Q2) The random process X(t) is called a white Gaussian noise process if X(t) is a stationary Gaussian random process with zero mean, and flat power spectral density, Let X(t) be a white Gaussian noise process that is input to...
Let Xn, -inf to +inf be a discrete-time zero-mean white noise process, i.e., μx[n] = 0, Rx[n] =δ[...
Let Xn, -inf to +inf be a discrete-time zero-mean white noise
process, i.e., μx[n] = 0, Rx[n] =δ[n]. The process is filtered
using an LTI system with impulse response
h[n] =αδ[n] + βδ[n−1].
Find α and β such that the output process Yn has autocorrelation
function Ry[n] =δ[n+1] + 2δ[n] +δ[n−1].
5) (3 points) Let Xn, -o0 K n oo, be a discrete-time zero-mean white noise process, i.e, ,1z[n]-(), Rx [n] S[n]. The process is filtered using an LTI system...
Problem 4 Let X(t), a continuous-time white noise process with zero mean and power spectral density equal to 2, be the...
Problem 4 Let X(t), a continuous-time white noise process with zero mean and power spectral density equal to 2, be the input to an LTI system with impulse response h(t)- 0 otherwise of Y (t). Sketch the autocorrelation function of Y(t)
Problem 4 Let X(t), a continuous-time white noise process with zero mean and power spectral density equal to 2, be the input to an LTI system with impulse response h(t)- 0 otherwise of Y (t). Sketch the autocorrelation function...
2. Let [et be a zero mean white noise process with variance 0.25. Suppose that the...
2. Let [et be a zero mean white noise process with variance 0.25. Suppose that the observed process is k = et + 0.5e-2. a. Explain why {Yt) is stationary. b. Compute yo-V(Y.) c. Compute the autocorrelation pkY, kl-0,1,2,... for Y) d. Let Wt = 3 + 4t + h. i. Find the mean of {W) ii. Is W3 stationary? Why or why not? iii. Let Z Vw, W,- W,_1. Is {Z.1 stationary? Why or why not?
2. Let (et) be a zero mean white noise process with variance 1. Suppose that the...
2. Let (et) be a zero mean white noise process with variance 1. Suppose that the observed process is h ft + Xt where β is an unknown constant, and Xt-et- Explain why {X.) is stationary. Find its mean function μχ and autocorrelation function p for lk0,1,.. a. b. Show that {Yt3 is not stationary. C. Explain why w. = ▽h = h-K-1 is stationary. d. Calculate Var(Yt) Vt and Var(W) Vt . (Recall: Var(X+c)-Var(X) when c is a constant.)...
2.4 Let (e) be a zero mean white noise process. Suppose that the observed process is...
2.4 Let (e) be a zero mean white noise process. Suppose that the observed process is Y = e, + 0,-1, where is either 3 or 1/3. (a) Find the autocorrelation function for {Y} both when 0 = 3 and when 0 = 1/3. (b) You should have discovered that the time series is stationary regardless of the value of and that the autocorrelation functions are the same for 0 = 3 and 0 = 1/3. For simplicity, suppose that...
uestion A causal, linear time-invariant system is excited with an input x (n) described as x(n)...
uestion A causal, linear time-invariant system is excited with an input x (n) described as x(n) 3u(n) with the output y(n) of the system as follows: 7l n) -2"u(n) y(n)- a) Determine z-transform X(z) and Y (z) (4 marks) b) Determine the transfer function H(z). (3 marks) Based on (b), determine the impulse response h(n). Based on (b), sketch the z-plane for the transfer function of the system Based on (d), determine the stability of the system and discuss the...
For a causal LTI discrete-time system described by the difference equation:
For a causal LTI discrete-time system described by the difference equation: y[n] + y[n – 1] = x[n] a) Find the transfer function H(z).b) Find poles and zeros and then mark them on the z-plane (pole-zero plot). Is this system BIBO? c) Find its impulse response h[n]. d) Draw the z-domain block diagram (using the unit delay block z-1) of the discrete-time system. e) Find the output y[n] for input x[n] = 10 u[n] if all initial conditions are 0.
A causal filter H(z) is excited by x(n) which is a white noise signal of zero mean 2 and unit variance. Its output is y(n). (28 points) H(2)05 Z-0.9 Give the autocorrelation of y(n) in closed form. Show all your work Give numerical values for ryy(0).1(1).1(2) a. b. Give the variance of y(n). c. Give the power spectral density (PSD) of y(n). d.
A causal filter H(z) is excited by x(n) which is a white noise signal of zero mean...
Let Xn, -inf to +inf be a discrete-time zero-mean white noise
process, i.e., μx[n] = 0, Rx[n] =δ[n]. The process is filtered
using an LTI system with impulse response
h[n] =αδ[n] + βδ[n−1].
Find α and β such that the output process Yn has autocorrelation
function Ry[n] =δ[n+1] + 2δ[n] +δ[n−1].
5) (3 points) Let Xn, -o0 K n oo, be a discrete-time zero-mean white noise process, i.e, ,1z[n]-(), Rx [n] S[n]. The process is filtered using an LTI system...
Problem 4 Let X(t), a continuous-time white noise process with zero mean and power spectral density equal to 2, be the input to an LTI system with impulse response h(t)- 0 otherwise of Y (t). Sketch the autocorrelation function of Y(t)
Problem 4 Let X(t), a continuous-time white noise process with zero mean and power spectral density equal to 2, be the input to an LTI system with impulse response h(t)- 0 otherwise of Y (t). Sketch the autocorrelation function...
2. Let [et be a zero mean white noise process with variance 0.25. Suppose that the observed process is k = et + 0.5e-2. a. Explain why {Yt) is stationary. b. Compute yo-V(Y.) c. Compute the autocorrelation pkY, kl-0,1,2,... for Y) d. Let Wt = 3 + 4t + h. i. Find the mean of {W) ii. Is W3 stationary? Why or why not? iii. Let Z Vw, W,- W,_1. Is {Z.1 stationary? Why or why not?
2. Let (et) be a zero mean white noise process with variance 1. Suppose that the observed process is h ft + Xt where β is an unknown constant, and Xt-et- Explain why {X.) is stationary. Find its mean function μχ and autocorrelation function p for lk0,1,.. a. b. Show that {Yt3 is not stationary. C. Explain why w. = ▽h = h-K-1 is stationary. d. Calculate Var(Yt) Vt and Var(W) Vt . (Recall: Var(X+c)-Var(X) when c is a constant.)...
2.4 Let (e) be a zero mean white noise process. Suppose that the observed process is Y = e, + 0,-1, where is either 3 or 1/3. (a) Find the autocorrelation function for {Y} both when 0 = 3 and when 0 = 1/3. (b) You should have discovered that the time series is stationary regardless of the value of and that the autocorrelation functions are the same for 0 = 3 and 0 = 1/3. For simplicity, suppose that...
uestion A causal, linear time-invariant system is excited with an input x (n) described as x(n) 3u(n) with the output y(n) of the system as follows: 7l n) -2"u(n) y(n)- a) Determine z-transform X(z) and Y (z) (4 marks) b) Determine the transfer function H(z). (3 marks) Based on (b), determine the impulse response h(n). Based on (b), sketch the z-plane for the transfer function of the system Based on (d), determine the stability of the system and discuss the...
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