(New page: Category: ECE Category: HKN Category: QE Category: Automatic Controls Category: Linear Systems =Problem 1= X and Y are iid <math> P(X=i) = P(Y=i) = \frac {1}{2^i}...)
 
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==Part A==
 
==Part A==
    Find <math> P(min(X,Y)=k)\ </math>
+
*Find <math> P(min(X,Y)=k)\ </math>
  
 
     Let <math> Z = min(X,Y)\ </math>
 
     Let <math> Z = min(X,Y)\ </math>
  
Then finding the pmf of Z uses the fact that X and Y are iid
+
    Then finding the pmf of Z uses the fact that X and Y are iid
    <math> P(Z=k) = P(X \ge k,Y \ge k) = P(X \ge k)P(Y \ge k) = P(X \ge k)^2 </math>
+
        <math> P(Z=k) = P(X \ge k,Y \ge k) = P(X \ge k)P(Y \ge k) = P(X \ge k)^2 </math>
  
    <math> P(Z=k) = \left ( \sum_{i=k}^N \frac {1}{2^i} \right )^2 = \left ( \frac {1}{2^k} \right )^2 = \frac {1}{4^k} </math>
+
        <math> P(Z=k) = \left ( \sum_{i=k}^N \frac {1}{2^i} \right )^2 = \left ( \frac {1}{2^k} \right )^2 = \frac {1}{4^k} </math>
 +
 
 +
==Part B==
 +
*Find <math> P(X=Y)\ </math>
 +
 
 +
    Noting that X and Y are iid and summing across all possible i,
 +
        <math> P(X=Y) = \sum_{i=1}^\infty P(X=i, Y=i) = \sum_{i=1}^\infty P(X=i)P(Y=i) = \sum_{i=1}^\infty \frac {1}{4^i} = \frac {1}{3} </math>
 +
 
 +
==Part C==
 +
*Find <math> P(Y>X)\ </math>
 +
 
 +
    Again noting that X and Y are iid and summing across all possible i,
 +
        <math> P(Y>X) = \sum_{i=1}^\infty P(Y>i, X=i) = \sum_{i=1}^\infty P(Y>i)P(x=i)</math>
 +
 
 +
    Next, find <math> P(Y<i)\ </math>
 +
        <math> P(Y>i) = 1 - P(Y \le i) </math>
 +
 
 +
        <math> P(Y \le i) = \sum_{i=1}^\infty \frac {1}{2^i} = 1 + \frac {1}{2^i} </math>
 +
 
 +
      <math> \therefore P(Y>i) = \frac {1}{2^i} </math>

Revision as of 10:20, 3 December 2008


Problem 1

X and Y are iid

   $  P(X=i) = P(Y=i) = \frac {1}{2^i}\ ,i = 1,2,3,...  $

Part A

  • Find $ P(min(X,Y)=k)\ $
   Let $  Z = min(X,Y)\  $
   Then finding the pmf of Z uses the fact that X and Y are iid
       $  P(Z=k) = P(X \ge k,Y \ge k) = P(X \ge k)P(Y \ge k) = P(X \ge k)^2  $
       $  P(Z=k) = \left ( \sum_{i=k}^N \frac {1}{2^i} \right )^2 = \left ( \frac {1}{2^k} \right )^2 = \frac {1}{4^k}  $

Part B

  • Find $ P(X=Y)\ $
   Noting that X and Y are iid and summing across all possible i,
       $  P(X=Y) = \sum_{i=1}^\infty P(X=i, Y=i) = \sum_{i=1}^\infty P(X=i)P(Y=i) = \sum_{i=1}^\infty \frac {1}{4^i} = \frac {1}{3}  $

Part C

  • Find $ P(Y>X)\ $
   Again noting that X and Y are iid and summing across all possible i,
       $  P(Y>X) = \sum_{i=1}^\infty P(Y>i, X=i) = \sum_{i=1}^\infty P(Y>i)P(x=i) $
   Next, find $  P(Y<i)\  $
       $  P(Y>i) = 1 - P(Y \le i)  $
       $  P(Y \le i) = \sum_{i=1}^\infty \frac {1}{2^i} = 1 + \frac {1}{2^i}  $
     $  \therefore P(Y>i) = \frac {1}{2^i}  $

Alumni Liaison

Ph.D. on Applied Mathematics in Aug 2007. Involved on applications of image super-resolution to electron microscopy

Francisco Blanco-Silva