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CDF: F<sub>X</sub>(x) = <math>1-e^{-\lambda*x}</math>
 
CDF: F<sub>X</sub>(x) = <math>1-e^{-\lambda*x}</math>
 +
 +
 +
PDF Properties
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* <math> f_X(x)\geq 0 </math> for all x
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* <math> \int\limits_{-\infty}^{\infty}f_X(x)dx = 1</math>
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* If <math> \delta </math> is very small, then
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  <math> P([x,x+\delta]) \approx f_X(x)\cdot\delta</math>
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* For any subset B of the real line,
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  <math> P(X\in B) = \int\limits_Bf_X(x)dx </math>

Revision as of 08:27, 20 October 2008

Cumulative Density Function (CDF)

  • FX(x) = P(X <= x) = integral(-inf to inf) fX(y) dy
  • 1 - FX(x) = P(X > x)


Exponential RV

PDF: fX(x) = $ \lambda*e^{-\lambda*x} $, x >= 0 ; fX(x) = 0 , else

CDF: FX(x) = $ 1-e^{-\lambda*x} $


PDF Properties

  • $ f_X(x)\geq 0 $ for all x
  • $ \int\limits_{-\infty}^{\infty}f_X(x)dx = 1 $
  • If $ \delta $ is very small, then
 $  P([x,x+\delta]) \approx f_X(x)\cdot\delta $
  • For any subset B of the real line,
 $  P(X\in B) = \int\limits_Bf_X(x)dx  $

Alumni Liaison

Sees the importance of signal filtering in medical imaging

Dhruv Lamba, BSEE2010