(New page: To find cov(X,Y) E[XY]=E[(Y+N)*Y]=E[Y^2]+E[Y]*E[N] (Y and N are independent) E[Y^2]= var[Y]-(E[Y])^2= 0 E[XY]=0 cov(X,Y)=E[XY]-E[X]*E[Y]= - (1/lamda)^2 I solve cov(X,Y) in this way...)
 
 
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To find cov(X,Y)  
 
To find cov(X,Y)  
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E[XY]=E[(Y+N)*Y]=E[Y^2]+E[Y]*E[N] (Y and N are independent)
 
E[XY]=E[(Y+N)*Y]=E[Y^2]+E[Y]*E[N] (Y and N are independent)
  

Latest revision as of 19:41, 9 December 2008

To find cov(X,Y)

E[XY]=E[(Y+N)*Y]=E[Y^2]+E[Y]*E[N] (Y and N are independent)

E[Y^2]= var[Y]-(E[Y])^2= 0

E[XY]=0

cov(X,Y)=E[XY]-E[X]*E[Y]= - (1/lamda)^2

I solve cov(X,Y) in this way. Is it right ??

Alumni Liaison

BSEE 2004, current Ph.D. student researching signal and image processing.

Landis Huffman