Line 30: Line 30:
  
 
<math>
 
<math>
E((X_i-S_n)S_n)=E(X_iS_n-S_n^2)=E(X_i-\frac{1}{n}\sum_k^n X_k)  
+
E((X_i-S_n)S_n)=E(X_iS_n-S_n^2)
 
</math>
 
</math>
  
 
As for any <math> i,j\in \{1,2,...,n\} </math>, we have <math>E(X_i\cdot X_j) = E(X_i)E(X_j)=0 </math>
 
As for any <math> i,j\in \{1,2,...,n\} </math>, we have <math>E(X_i\cdot X_j) = E(X_i)E(X_j)=0 </math>
 +
 +
<math>
 +
E(X_iS_n-S_n^2) = E(X_iS_n)-E(S_n^2)\\
 +
=E(\sum_k^nX_iX_K) - E(\sum_i^n\sum_k^nX_iX_K)
 +
=\sum_k^nE(X_iX_K) - \sum_i^n\sum_k^nE(X_iX_K) \\
 +
=0
 +
</math>
 +
 +
Thus <math>E(X_i-S_n]E(S_n)=E((X_i-S_n)S_n)</math>, <math>S_n</math> and <math>X_i-S_n</math> are uncorrelated.
 
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[[ECE-QE_CS1-2015|Back to QE CS question 1, August 2015]]
 
[[ECE-QE_CS1-2015|Back to QE CS question 1, August 2015]]
  
 
[[ECE_PhD_Qualifying_Exams|Back to ECE Qualifying Exams (QE) page]]
 
[[ECE_PhD_Qualifying_Exams|Back to ECE Qualifying Exams (QE) page]]

Revision as of 01:12, 4 December 2015


ECE Ph.D. Qualifying Exam

Communication, Networking, Signal and Image Processing (CS)

Question 1: Probability and Random Processes

August 2015


$ E(S_n)=E(\frac{1}{n}\sum_i^n X_i) =\frac{1}{n}\sum_i^n E(X_i)=0 $

$ E(X_i-S_n)=E(X_i-\frac{1}{n}\sum_k^n X_k) =E(X_i)-E(\frac{1}{n}\sum_k^n X_k)=0 $

$ E((X_i-S_n)S_n)=E(X_iS_n-S_n^2) $

As for any $ i,j\in \{1,2,...,n\} $, we have $ E(X_i\cdot X_j) = E(X_i)E(X_j)=0 $

$ E(X_iS_n-S_n^2) = E(X_iS_n)-E(S_n^2)\\ =E(\sum_k^nX_iX_K) - E(\sum_i^n\sum_k^nX_iX_K) =\sum_k^nE(X_iX_K) - \sum_i^n\sum_k^nE(X_iX_K) \\ =0 $

Thus $ E(X_i-S_n]E(S_n)=E((X_i-S_n)S_n) $, $ S_n $ and $ X_i-S_n $ are uncorrelated.


Back to QE CS question 1, August 2015

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Correspondence Chess Grandmaster and Purdue Alumni

Prof. Dan Fleetwood