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+ | [[Category:probability]] | ||
− | = [[ECE_PhD_Qualifying_Exams|ECE Ph.D. Qualifying Exam]] | + | <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== | ||
− | + | '''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> . | ||
+ | |||
+ | |||
+ | :'''Click [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.1|here]] to view student [[ECE_PhD_QE_CNSIP_Jan_2004_Problem1.1|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 <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]]''' | ||
---- | ---- | ||
− | == | + | '''3. (30 pts.)''' |
− | Write | + | |
+ | 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]]''' | ||
+ | ---- | ||
+ | '''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) | ||
+ | |||
+ | 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]]''' | ||
---- | ---- | ||
[[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
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