Section 6.5: Mean Square Estimation 6.68. Let X and Y be discrete random variables with three possible joint pmf's: Let X and Y have joint pdf: fx.y(x, y) -k(x + y) for 0 sxs 1,0s ys1 F...
6.72 Let Y =X+N where X and N are independent Gaussian random variables with different variance and N is zero mean. (a) Plot the correlation coefficient between the “observed signal” Y and the “desired signal” X as a funtion of the signal-to-noise ratio (b) Find the minimum mean square error estimator for X given Y (c)Find the MAP and ML estimators for X given Y (d) Compare the mean square error of the estimators in parts a, b, and c.
Let X and Y be two jointly continuous random variables with joint PDF xy0x, y < 1 fxy (x, y) O.W Find the MAP and ML estimates of X given Y = y
Consider the joint PDF of two random variables X and Y below. fx.y (x y) = 1, if 0 < x < 1, and 0 y< 1, and fxx (г, у) Oif andy are outside of that square. So, basically, the joint PDF is a constant over the unit square Let W X+Y. Suppose we express the CDF of W in the usual double integral form h Fw(W) 2 dy dx g where w-0.4 is a given value at which...
2. Let X and Y be continuous random variables with joint pdf fx.y (x. y)- 3x, 0 Syx, and zero otherwise. a. b. c. d. e. What is the marginal pdf of X? What is the marginal pdf of Y? What is the expectation of X alone? What is the covariance of X and Y? What is the correlation of X and Y?
Let the random variables X, Y with joint probability density function (pdf) fxy(z, y) = cry, where 0 < y < z < 2. (a) Find the value of c that makes fx.y (a, y) a valid pdf. (b) Calculate the marginal density functions for X and Y (c) Find the conditional density function of Y X (d) Calculate E(X) and EYIX) (e Show whether X. Y are independent or not.
Two random variables are jointly distributed with joint pdf given by: = 0, elsewhere a) Find the value of K? b) Find the best LMMSE of Y. what is the MMSE error in this case? c) Find the best MMSE estimator of Y? d) What is minimum mean square error of Y given that x -1 Two random variables are jointly distributed with joint pdf given by: = 0, elsewhere a) Find the value of K? b) Find the best...
. For > 0 and A > 0, define the joint pdf -Ay = 0<x<A,<y, fx.y(,y) 10 else. (a) Express c in terms of X and A. (b) Find E[XY]. (c) Let [2] be the largest integer less than or equal to z. For example, (3.2] = 3 and [2] = 2. Find the probability that [Y] is even, given that 4 <x< 34
55. Let X and Y be jointly continuous random variables with joint density function fx.y(x,y) be-3y -a < x < 2a, 0) < y < 00, otherwise. Assume that E[XY] = 1/6. (a) Find a and b such that fx,y is a valid joint pdf. You may want to use the fact that du = 1. u 6. и е (b) Find the conditional pdf of X given Y = y where 0 <y < . (c) Find Cov(X,Y). (d)...
2. Let the random variables X and Y have the joint PDF given below: 2e -y 0 xyo0 fxy (x, y) otherwise 0 (a) Find P(X Y < 2) (b) Find the marginal PDFs of X and Y (c) Find the conditional PDF of Y X x (d) Find P(Y< 3|X = 1)
The random variables X and Y have the joint PDF -fa.. 2 0 S x s 1 0 Sy s1 (2х + Зу) fxy(x, y) = otherwise The mean squared error is defined as ET(X + Y - t)21, what value of t minimizes this error? The random variables X and Y have the joint PDF -fa.. 2 0 S x s 1 0 Sy s1 (2х + Зу) fxy(x, y) = otherwise The mean squared error is defined as...