Problem 4 Let X(t), a continuous-time white noise process with zero mean and power spectral density equal to 2, be the...
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...
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...
Problem 5 (LSM5) (20 pts) A WSS noise process z(t) with power spectral density Ser(ju) VAre is passed through an LTI system with frequency response H(ju) 2 Denote the output of the systeru by y(t). Determine the following: (a) The correlation function R ) of r; (b) The power P, of a; (c) The power spectral density Sy ju) of y. Note: Problem 5 (LSM5) (20 pts) A WSS noise process z(t) with power spectral density Ser(ju) VAre is passed...
5.57 Let np(t) be a zero-mean white Gaussian noise with the power spectral density 20 let this noise be passed through an ideal bandpass filter with the bandwidth 2W centered at the frequency fe. Denote the output process by nt). 1. Assuming fo fe, find the power content of the in-phase and quadrature components of n(t). We were unable to transcribe this image 5.57 Let np(t) be a zero-mean white Gaussian noise with the power spectral density 20 let this...
Please respond as soon as possible, thank you. An LTI system has the impulse response h(T) = 1 for 0 <T<T and is zero otherwise. If continuous-time white noise with ACF ru(T) = (No/2)8(T) is input to the system, what is the PSD of the output random process? Sketch the PSD.
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...
2. 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 ry(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...
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...
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?
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...