9] 2. Let(X")}, (X12Ί, . . . , { with spectral densities f:i) (w) for-1, 2, . . . , n. Let Xbe n ...
I. (5 points) Let {X, } be a stationary series with mean μ and autocovariance function 7(), and icz Show Y is also stationary for a, ER, iE Z 2. (5 points) Let {Xi be the process Xi A cos(wt) Bsin(t),t 1,2, ., COS
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) Let the cross-correlation function of two processes X(t) and Y(t) be where A, B, and ω are constants. Find the cross-power spectral density, SXY(ω). (Hint: you'll need to find the time average of R first) 2) Let the cross-correlation function of two processes X(t) and Y(t) be where A, B, and ω are constants. Find the cross-power spectral density, SXY(ω). (Hint: you'll need to find the time average of R first)
3.34. Let fXc(t)) and (X,(t)J denote two statistically independent zero n stationary Gaussian random processes with common power spec- tral density given by SX (f) = SX (f) = 112B(f) watt/Hz. Define x(t) = Xe(t) cos(2tht)--Xs(t) sin(2tht) where fo 》 (a) Is X(t) a Gaussian process? (b) Find the mean E(X (t), autocorrelation function Rx (t,t + T), and power spectral density Sx(f) of the process X(t) (c) Find the pdf of X(O) (d) The process X(t) is passed through...
7.3-2. A random process is given by W(t) = AX(t) + BY(1) where A and B are real constants and X(t) and Y(t) are jointly wide-sense stationary processes. (a) Find the power spectrum S www) of W(t). (b) Find S www if X(t) and Y(t) are uncorrelated. (c) Find the cross-power spectrums S xw(w) and S yw(w).
Let X, , x, be a random sample from some density which has mean μ and variance σ2. Show that Σ a, X, is an unbiased estimator of/e for any set of known constants a, , . . . , a, satisfying Σ a,-1. If Σ a.-1, show that var [ Σ a, xl] is minimized for ai = 1/n, i = 1, [HINT: Prove that Σ a-Σ (al-IMF + 1/n when Σ al = 1 .] (a) (b) ,...
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. Consider the time series X, = 2 + 0.5t +0.8X1-1 + W, where W N(0.1). (a) (8 points) Calculate E(X2) Is this process weakly stationary? Give reasons for your answer. Hint: Find the mean function of {X) and then substitute t = 20. (b) (3 points) Calculate Var(X20) Question 2 continues on the next page... Page 4 of 12 c)(4 points) Consider the first differences of the time series above, that is Is {%) a weakly stationary process. Prove...
(a) If var[X o2 for each Xi (i = 1,... ,n), find the variance of X = ( Xi)/n. (b) Let the continuous random variable Y have the moment generating function My (t) i. Show that the moment generating function of Z = aY b is e*My(at) for non-zero constants a and b ii. Use the result to write down the moment generating function of W 1- 2X if X Gamma(a, B) (a) If var[X o2 for each Xi (i...
#2 2. Let X, N o ?) for i=1,2. Show that Y = X1 + X, and Z X; - X2 are independent. 3. Let 2-N(0,1) and W x (n) with Z be independent of W. Show that the distribution of T- tudiatvihustion with n deerees of freedom. (Hint: create a second variable U - find the joint distribution