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The opposite or complement of an event A is(that is, the event of A not occurring)is
 
 
    <math>P(A') = 1 - P(A)\,</math>
 
 
If two events, A and B are independent then the joint probability is
 
 
    <math>P(A \mbox{ and }B) =  P(A \cap B) = P(A) P(B)\,</math>
 
 
If two events are mutually exclusive then the probability of either occurring is
 
 
    <math>P(A\mbox{ or }B) =  P(A \cup B)= P(A) + P(B)</math>
 
 
 
If the events are not mutually exclusive then
 
If the events are not mutually exclusive then
  
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{|
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! colspan="2" style="background:  #e4bc7e; font-size: 110%;" | Discrete-time Fourier Transform Pairs and Properties
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|-
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! colspan="2" style="background: #eee;" | Property of Probability Functions
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|-
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| align="right" style="padding-right: 1em;" | The complement of an event A (i.e. the event A not occurring) || <math>\,P(A^c) = 1 - P(A)\,</math>
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|-
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| align="right" style="padding-right: 1em;" | The intersection of two independent events A and B || <math>\,P(A \mbox{ and }B) =  P(A \cap B) = P(A) P(B)\,</math>
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|-
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| align="right" style="padding-right: 1em;" | The union of two events A and B (i.e. either A or B occurring) || <math>\,P(A \mbox{ or } B) = P(A) + P(B) - P(A \mbox{ and } B)\,</math>
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|-
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| align="right" style="padding-right: 1em;" | The union of two mutually exclusive events A and B || <math>\,P(A \mbox{ or } B) =  P(A \cup B)= P(A) + P(B)\,</math>
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|}
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{|
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|-
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! colspan="4" style="background: #eee;" | DT Fourier Transform Pairs
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|-
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| align="right" style="padding-right: 1em;" |  || <math>x[n]</math> || <math>\longrightarrow</math>|| <math> \mathcal{X}(\omega) </math>
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|-
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| align="right" style="padding-right: 1em;" | DTFT of a complex exponential || <math>e^{jw_0n}</math> || || <math>\pi\sum_{l=-\infty}^{+\infty}\delta(w-w_0-2\pi l) \ </math>
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|-
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|-
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| align="right" style="padding-right: 1em;" |  || <math>a^{n} u[n],  |a|<1 \ </math> || ||<math>\frac{1}{1-ae^{-j\omega}} \ </math>
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|-
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| align="right" style="padding-right: 1em;" |  || <math>\sin\left(\omega _0 n\right) u[n] \ </math>  || ||<math>\frac{1}{2j}\left( \frac{1}{1-e^{-j(\omega -\omega _0)}}-\frac{1}{1-e^{-j(\omega +\omega _0)}}\right)</math>
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|-
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|}
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{|
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|-
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! colspan="4" style="background: #eee;" | DT Fourier Transform Properties
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|-
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| align="right" style="padding-right: 1em;" |  || <math>x[n]</math> || <math>\longrightarrow</math>|| <math> \mathcal{X}(\omega) </math>
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|-
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| align="right" style="padding-right: 1em;" | multiplication property|| <math>x[n]y[n] \ </math> || || <math>\frac{1}{2\pi} \int_{2\pi} X(\theta)Y(\omega-\theta)d\theta</math>
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|-
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| align="right" style="padding-right: 1em;" |  convolution property || <math>x[n]*y[n] \!</math> || ||<math> X(\omega)Y(\omega) \!</math>
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|-
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| align="right" style="padding-right: 1em;" | time reversal ||<math>\ x[-n] </math> || ||<math>\ X(-\omega)</math>
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|-
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|}
  
...More to come.
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{|
And you can contribute too, simply click on edit in the page actions menu and start typing away!!
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|-
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! colspan="2" style="background: #eee;" | Other DT Fourier Transform Properties
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|-
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| align="right" style="padding-right: 1em;" | Parseval's relation  || <math>\frac {1}{N} \sum_{n=-\infty}^{\infty}\left| x[n] \right|^2 = </math>
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|}
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----
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[[Collective_Table_of_Formulas|Back to Collective Table]]
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[[Category:Formulas]]

Revision as of 08:51, 22 October 2010

If the events are not mutually exclusive then

   $ \mathrm{P}\left(A \hbox{ or } B\right)=\mathrm{P}\left(A\right)+\mathrm{P}\left(B\right)-\mathrm{P}\left(A \mbox{ and } B\right) $

Conditional probability is written P(A|B), and is read "the probability of A, given B"

   $ P(A \mid B) = \frac{P(A \cap B)}{P(B)}\, $


Discrete-time Fourier Transform Pairs and Properties
Property of Probability Functions
The complement of an event A (i.e. the event A not occurring) $ \,P(A^c) = 1 - P(A)\, $
The intersection of two independent events A and B $ \,P(A \mbox{ and }B) = P(A \cap B) = P(A) P(B)\, $
The union of two events A and B (i.e. either A or B occurring) $ \,P(A \mbox{ or } B) = P(A) + P(B) - P(A \mbox{ and } B)\, $
The union of two mutually exclusive events A and B $ \,P(A \mbox{ or } B) = P(A \cup B)= P(A) + P(B)\, $
DT Fourier Transform Pairs
$ x[n] $ $ \longrightarrow $ $ \mathcal{X}(\omega) $
DTFT of a complex exponential $ e^{jw_0n} $ $ \pi\sum_{l=-\infty}^{+\infty}\delta(w-w_0-2\pi l) \ $
$ a^{n} u[n], |a|<1 \ $ $ \frac{1}{1-ae^{-j\omega}} \ $
$ \sin\left(\omega _0 n\right) u[n] \ $ $ \frac{1}{2j}\left( \frac{1}{1-e^{-j(\omega -\omega _0)}}-\frac{1}{1-e^{-j(\omega +\omega _0)}}\right) $
DT Fourier Transform Properties
$ x[n] $ $ \longrightarrow $ $ \mathcal{X}(\omega) $
multiplication property $ x[n]y[n] \ $ $ \frac{1}{2\pi} \int_{2\pi} X(\theta)Y(\omega-\theta)d\theta $
convolution property $ x[n]*y[n] \! $ $ X(\omega)Y(\omega) \! $
time reversal $ \ x[-n] $ $ \ X(-\omega) $
Other DT Fourier Transform Properties
Parseval's relation $ \frac {1}{N} \sum_{n=-\infty}^{\infty}\left| x[n] \right|^2 = $

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