(→Problem 1: Random Point, Revisited) |
(→Problem 2: Variable Dependency) |
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== Problem 2: Variable Dependency== | == Problem 2: Variable Dependency== | ||
| + | Suppose that <math>X</math> and <math>Y</math> are zero-mean jointly Gaussian random variables with variances <math>\sigma_X^2</math> and <math>\sigma_Y^2</math>, respectively and correlation coefficient <math>\rho</math>. | ||
| + | \begin{enumerate} | ||
| + | \item Find the means and variances of the random variables <math>Z = X\cos\theta + Y\sin\theta</math> and <math>W = Y\cos\theta - X sin\theta</math>. | ||
| + | \item What is <math>Cov(Z,W)</math>? | ||
| + | \item Find an angle <math>\theta</math> such that <math>Z</math> and <math>W</math> are independent Gaussian random variables. You may express your answer as a trigonometric function involving <math>\sigma_X^2</math>, <math>\sigma_Y^2</math>, and <math>\rho</math>. In particular,what is the value of <math>\theta</math> if <math>\sigma_X = \sigma_Y</math>? | ||
== Problem 3: Noisy Measurement== | == Problem 3: Noisy Measurement== | ||
== Problem 4: Digital Loss== | == Problem 4: Digital Loss== | ||
Revision as of 07:06, 2 December 2008
Contents
Instructions
Homework 10 can be downloaded here on the ECE 302 course website.
Problem 1: Random Point, Revisited
In the following problems, the random point (X , Y) is uniformly distributed on the shaded region shown.
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- (a) Find the marginal pdf $ f_X(x) $ of the random variable $ X $. Find $ E[X] $ and $ Var(X) $.
- (b) Using your answer from part (a), find the marginal pdf $ f_Y(y) $ of the random variable $ Y $, and its mean and variance, $ E[Y] $, and $ Var[Y] $.
- (c) Find $ f_{Y|X}(y|\alpha) $, the conditional pdf of $ Y $ given that $ X = \alpha $, where $ 0 < \alpha < 1/2 $. Then find the conditional mean and conditional variance of $ Y $ given that $ X = \alpha $.
- (d) What is the MMSE estimator, $ \hat{y}_{\rm MMSE}(x) $?
- (e) What is the Linear MMSE estimator, $ \hat{y}_{\rm LMMSE}(x) $?
Problem 2: Variable Dependency
Suppose that $ X $ and $ Y $ are zero-mean jointly Gaussian random variables with variances $ \sigma_X^2 $ and $ \sigma_Y^2 $, respectively and correlation coefficient $ \rho $. \begin{enumerate} \item Find the means and variances of the random variables $ Z = X\cos\theta + Y\sin\theta $ and $ W = Y\cos\theta - X sin\theta $. \item What is $ Cov(Z,W) $? \item Find an angle $ \theta $ such that $ Z $ and $ W $ are independent Gaussian random variables. You may express your answer as a trigonometric function involving $ \sigma_X^2 $, $ \sigma_Y^2 $, and $ \rho $. In particular,what is the value of $ \theta $ if $ \sigma_X = \sigma_Y $?
