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===== <math>\color{blue}\text{Solution 2:}</math>  =====
 
===== <math>\color{blue}\text{Solution 2:}</math>  =====
 +
'''(a)'''
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<br>
 +
Since <math class="inline">\mathbf{Y}_{n} = min \,\{{ \mathbf{X}_1, \mathbf{X}_2, \dots \mathbf{X}_n} \},</math>
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<br>
 +
We can have the CDF of <math class="inline">\mathbf{Y}_{n}</math>
 +
<br>
 +
<math> P(\mathbf{Y}_{n} \leq y) = P(\,\{{ \mathbf{X}_1, \mathbf{X}_2, \dots \mathbf{X}_n} \} \leq y) </math> <br>
 +
<math> = 1-P(\,\{{ \mathbf{X}_1, \mathbf{X}_2, \dots \mathbf{X}_n} \} > y)</math><br>
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<math> = 1-P(\mathbf{X}_1 > y)P(\mathbf{X}_2 > y) \dots P(\mathbf{X}_n > y)</math><br>
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<math> = 1-(1-F_{X_1}(y))(1-F_{X_2}(y)) \dots (1-F_{X_n}(y))=1-(1-F_{X_1}(y))^n</math><br>
 +
 +
Since <math class="inline">\mathbf{Y}_{n} </math> is also uniform distributed on the interval [0,1] <br>
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When <math class="inline"> y <0 </math>, <math class="inline">P(\{\mathbf{Y}_{n}<0 \}) =0 </math>  since <math class="inline">F_{X_1}(y) =0 </math><br>

Revision as of 17:41, 25 January 2014


ECE Ph.D. Qualifying Exam

Communication, Networking, Signal and Image Processing (CS)

Question 1: Probability and Random Processes

August 2012



Jump to Problem 2,3


Problem 3

$ \color{blue}\text{Solution 1:} $
$ \color{blue}\text{Solution 2:} $

(a)
Since $ \mathbf{Y}_{n} = min \,\{{ \mathbf{X}_1, \mathbf{X}_2, \dots \mathbf{X}_n} \}, $
We can have the CDF of $ \mathbf{Y}_{n} $
$ P(\mathbf{Y}_{n} \leq y) = P(\,\{{ \mathbf{X}_1, \mathbf{X}_2, \dots \mathbf{X}_n} \} \leq y) $
$ = 1-P(\,\{{ \mathbf{X}_1, \mathbf{X}_2, \dots \mathbf{X}_n} \} > y) $
$ = 1-P(\mathbf{X}_1 > y)P(\mathbf{X}_2 > y) \dots P(\mathbf{X}_n > y) $
$ = 1-(1-F_{X_1}(y))(1-F_{X_2}(y)) \dots (1-F_{X_n}(y))=1-(1-F_{X_1}(y))^n $

Since $ \mathbf{Y}_{n} $ is also uniform distributed on the interval [0,1]
When $ y <0 $, $ P(\{\mathbf{Y}_{n}<0 \}) =0 $ since $ F_{X_1}(y) =0 $

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