| Line 13: | Line 13: | ||
<div style="margin-left: 25em;"> | <div style="margin-left: 25em;"> | ||
| − | <math> /mu = \varepsilon | + | <math>/mu = \varepsilon[x] = \int\limits_{-/infty}^{/infty} xp(x)\, dx</math> |
</div> | </div> | ||
Revision as of 15:58, 4 April 2013
Discriminant Functions For The Normal Density
Lets begin with the continuous univariate normal or Gaussian density.
$ f_x = \frac{1}{\sqrt{2 \pi} \sigma} \exp \left [- \frac{1}{2} \left ( \frac{x - \mu}{\sigma} \right)^2 \right ] $
for which the expected value of x is
$ /mu = \varepsilon[x] = \int\limits_{-/infty}^{/infty} xp(x)\, dx $
