(New page: <math>x[n] = 2 + cos(\omega_0 n) + 4sin(\omega_0 n + \frac{\pi}{2})</math> where <math>\omega_0 = \frac{2\pi}{N}</math>. <math>h[n] = x[n] * \delta[n] = </math>)
 
 
(One intermediate revision by the same user not shown)
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<math>x[n] = 2 + cos(\omega_0 n) + 4sin(\omega_0 n + \frac{\pi}{2})</math>  
+
<math>y[n] = x[n] + x[n -1]</math>  
  
where <math>\omega_0 = \frac{2\pi}{N}</math>.
+
<math>h[n] = \delta[n] + \delta[n-1]</math>
  
<math>h[n] = x[n] * \delta[n] = </math>
+
<math>H[z] = \sum_{k=-\infty}^\infty h[k] z^{-k}</math>
 +
 
 +
<math> = \sum_{k=0}^1 h[k] z^{-k}</math>
 +
 
 +
when k = 0, <math>H[z] = 1</math>
 +
 
 +
when k = 1, <math>H[z] = z^{-1}</math>
 +
 
 +
else, <math>H[z] = 0</math>

Latest revision as of 04:35, 26 September 2008

$ y[n] = x[n] + x[n -1] $

$ h[n] = \delta[n] + \delta[n-1] $

$ H[z] = \sum_{k=-\infty}^\infty h[k] z^{-k} $

$ = \sum_{k=0}^1 h[k] z^{-k} $

when k = 0, $ H[z] = 1 $

when k = 1, $ H[z] = z^{-1} $

else, $ H[z] = 0 $

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Sees the importance of signal filtering in medical imaging

Dhruv Lamba, BSEE2010