(2 intermediate revisions by one other user not shown)
Line 4: Line 4:
 
[[Category:problem solving]]
 
[[Category:problem solving]]
 
[[Category:random variables]]
 
[[Category:random variables]]
 +
[[Category:probability]]
  
= [[ECE_PhD_Qualifying_Exams|ECE Ph.D. Qualifying Exam]]: COMMUNICATIONS, NETWORKING, SIGNAL AND IMAGE PROESSING (CS)- Question 1, January 2004=
+
<center>
 +
<font size= 4>
 +
[[ECE_PhD_Qualifying_Exams|ECE Ph.D. Qualifying Exam]]
 +
</font size>
 +
 
 +
<font size= 4>
 +
Communication, Networking, Signal and Image Processing (CS)
 +
 
 +
Question 1: Probability and Random Processes
 +
</font size>
 +
 
 +
January 2004
 +
</center>
 +
----
 
----
 
----
 
==Question==
 
==Question==
'''Part 1. '''
+
'''1. (30 pts.)'''
 +
 
 +
This question consists of two separate short questions relating to the structure of probability space:
 +
 
 +
'''(a)'''
 +
 
 +
Assume that <math class="inline">\mathcal{S}</math>  is the sample space of a random experiment and that <math class="inline">\mathcal{F}_{1}</math>  and <math class="inline">\mathcal{F}_{2}</math>  are <math class="inline">\sigma</math> -fields (valid event spaces) on <math class="inline">\mathcal{S}</math> . Prove that <math class="inline">\mathcal{F}_{1}\cap\mathcal{F}_{2}</math>  is also a <math class="inline">\sigma</math> -field on <math class="inline">S</math> .
 +
 
 +
'''(b)'''
 +
 
 +
Consider a sample space <math class="inline">\mathcal{S}</math>  and corresponding event space <math class="inline">\mathcal{F}</math> . Suppose that <math class="inline">P_{1}</math>  and <math class="inline">P_{2}</math>  are both balid probability measures defined on <math class="inline">\mathcal{F}</math> . Prove that <math class="inline">P</math>  defined by <math class="inline">P\left(A\right)=\alpha_{1}P_{1}\left(A\right)+\alpha_{2}P_{2}\left(A\right),\qquad\forall A\in\mathcal{F}</math>  is also a valid probability measure on <math class="inline">\mathcal{F}</math>  if <math class="inline">\alpha_{1},\;\alpha_{2}\geq0</math>  and <math class="inline">\alpha_{1}+\alpha_{2}=1</math> .
  
Write Statement here
 
  
 
:'''Click [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.1|here]] to view student [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.1|answers and discussions]]'''
 
:'''Click [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.1|here]] to view student [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.1|answers and discussions]]'''
 
----
 
----
'''Part 2.'''
+
'''2. (10 pts.)'''
  
Write question here.
+
Identical twins come from the same egg and and hence are of the same sex. Fraternal twins have a probability <math class="inline">1/2</math>  of being of the same sex. Among twins, the probability of a fraternal set is p  and of an identical set is <math class="inline">q=1-p</math> . Given that a set of twins selected at random are of the same sex, what is the probability they are fraternal? (Simplify your answer as much as possible.) Sketch a plot of the conditional probability that the twins are fraternal given that they are of the same sex as a function of <math class="inline">q</math>  (the probability that a set of twins are identical.)
  
 
:'''Click [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.2|here]] to view student [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.2|answers and discussions]]'''
 
:'''Click [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.2|here]] to view student [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.2|answers and discussions]]'''
 
----
 
----
'''Part 3.'''
+
'''3. (30 pts.)'''
  
Write question here.
+
Let <math class="inline">\mathbf{X}\left(t\right)</math>  be a real continuous-time Gaussian random process. Show that its probabilistic behavior is completely characterized by its mean <math class="inline">\mu_{\mathbf{X}}\left(t\right)=E\left[\mathbf{X}\left(t\right)\right]</math> and its autocorrelation function <math class="inline">R_{\mathbf{XX}}\left(t_{1},t_{2}\right)=E\left[\mathbf{X}\left(t_{1}\right)\mathbf{X}\left(t_{2}\right)\right].</math>
  
 
:'''Click [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.3|here]] to view student [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.3|answers and discussions]]'''
 
:'''Click [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.3|here]] to view student [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.3|answers and discussions]]'''
 
----
 
----
'''Part 4.'''
+
'''4. (30 pts.)'''
 +
 
 +
Assume that <math class="inline">\mathbf{X}\left(t\right)</math>  is a zero-mean, continuous-time, Gaussian white noise process with autocorrelation function <math class="inline">R_{\mathbf{XX}}\left(t_{1},t_{2}\right)=\delta\left(t_{1}-t_{2}\right)</math>.  Let <math class="inline">\mathbf{Y}\left(t\right)</math>  be a new random process defined by <math class="inline">\mathbf{Y}\left(t\right)=\frac{1}{T}\int_{t-T}^{t}\mathbf{X}\left(s\right)ds</math>,  where <math class="inline">T>0</math> .
 +
 
 +
'''(a)'''
 +
 
 +
What is the mean of <math class="inline">\mathbf{Y}\left(t\right)</math> ?
 +
 
 +
'''(b)'''
 +
 
 +
What is the autocorrelation function of <math class="inline">\mathbf{Y}\left(t\right)</math> ?
 +
 
 +
'''(c)'''
 +
 
 +
Write an expression for the second-order pdf <math class="inline">f_{\mathbf{Y}\left(t_{1}\right)\mathbf{Y}\left(t_{2}\right)}\left(y_{1},y_{2}\right)</math>  of <math class="inline">\mathbf{Y}\left(t\right)</math> .
 +
 
 +
(d)
  
Write question here.
+
Under what conditions on <math class="inline">t_{1}</math>  and <math class="inline">t_{2}</math>  will <math class="inline">\mathbf{Y}\left(t_{1}\right)</math>  and <math class="inline">\mathbf{Y}\left(t_{2}\right)</math>  be statistically independent?
  
 
:'''Click [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.4|here]] to view student [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.4|answers and discussions]]'''
 
:'''Click [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.4|here]] to view student [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.4|answers and discussions]]'''
 
----
 
----
 
[[ECE_PhD_Qualifying_Exams|Back to ECE Qualifying Exams (QE) page]]
 
[[ECE_PhD_Qualifying_Exams|Back to ECE Qualifying Exams (QE) page]]

Latest revision as of 00:01, 10 March 2015


ECE Ph.D. Qualifying Exam

Communication, Networking, Signal and Image Processing (CS)

Question 1: Probability and Random Processes

January 2004



Question

1. (30 pts.)

This question consists of two separate short questions relating to the structure of probability space:

(a)

Assume that $ \mathcal{S} $ is the sample space of a random experiment and that $ \mathcal{F}_{1} $ and $ \mathcal{F}_{2} $ are $ \sigma $ -fields (valid event spaces) on $ \mathcal{S} $ . Prove that $ \mathcal{F}_{1}\cap\mathcal{F}_{2} $ is also a $ \sigma $ -field on $ S $ .

(b)

Consider a sample space $ \mathcal{S} $ and corresponding event space $ \mathcal{F} $ . Suppose that $ P_{1} $ and $ P_{2} $ are both balid probability measures defined on $ \mathcal{F} $ . Prove that $ P $ defined by $ P\left(A\right)=\alpha_{1}P_{1}\left(A\right)+\alpha_{2}P_{2}\left(A\right),\qquad\forall A\in\mathcal{F} $ is also a valid probability measure on $ \mathcal{F} $ if $ \alpha_{1},\;\alpha_{2}\geq0 $ and $ \alpha_{1}+\alpha_{2}=1 $ .


Click here to view student answers and discussions

2. (10 pts.)

Identical twins come from the same egg and and hence are of the same sex. Fraternal twins have a probability $ 1/2 $ of being of the same sex. Among twins, the probability of a fraternal set is p and of an identical set is $ q=1-p $ . Given that a set of twins selected at random are of the same sex, what is the probability they are fraternal? (Simplify your answer as much as possible.) Sketch a plot of the conditional probability that the twins are fraternal given that they are of the same sex as a function of $ q $ (the probability that a set of twins are identical.)

Click here to view student answers and discussions

3. (30 pts.)

Let $ \mathbf{X}\left(t\right) $ be a real continuous-time Gaussian random process. Show that its probabilistic behavior is completely characterized by its mean $ \mu_{\mathbf{X}}\left(t\right)=E\left[\mathbf{X}\left(t\right)\right] $ and its autocorrelation function $ R_{\mathbf{XX}}\left(t_{1},t_{2}\right)=E\left[\mathbf{X}\left(t_{1}\right)\mathbf{X}\left(t_{2}\right)\right]. $

Click here to view student answers and discussions

4. (30 pts.)

Assume that $ \mathbf{X}\left(t\right) $ is a zero-mean, continuous-time, Gaussian white noise process with autocorrelation function $ R_{\mathbf{XX}}\left(t_{1},t_{2}\right)=\delta\left(t_{1}-t_{2}\right) $. Let $ \mathbf{Y}\left(t\right) $ be a new random process defined by $ \mathbf{Y}\left(t\right)=\frac{1}{T}\int_{t-T}^{t}\mathbf{X}\left(s\right)ds $, where $ T>0 $ .

(a)

What is the mean of $ \mathbf{Y}\left(t\right) $ ?

(b)

What is the autocorrelation function of $ \mathbf{Y}\left(t\right) $ ?

(c)

Write an expression for the second-order pdf $ f_{\mathbf{Y}\left(t_{1}\right)\mathbf{Y}\left(t_{2}\right)}\left(y_{1},y_{2}\right) $ of $ \mathbf{Y}\left(t\right) $ .

(d)

Under what conditions on $ t_{1} $ and $ t_{2} $ will $ \mathbf{Y}\left(t_{1}\right) $ and $ \mathbf{Y}\left(t_{2}\right) $ be statistically independent?

Click here to view student answers and discussions

Back to ECE Qualifying Exams (QE) page

Alumni Liaison

Basic linear algebra uncovers and clarifies very important geometry and algebra.

Dr. Paul Garrett