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== Answer ==
 
== Answer ==
<math> y[n] = x[n] * h[n] , where * is convolution,/</math>
+
<math> y[n] = x[n] * h[n] , where * is convolution/,</math>
  
 
<math> \sum^{\infty}_{k=-\infty} 2^{k}u[-k]u[-n+k]</math>
 
<math> \sum^{\infty}_{k=-\infty} 2^{k}u[-k]u[-n+k]</math>
 +
 +
<math> \sum^{0}_{k=-\infty} 2^{k}u[-n+k]</math>
 +
 +
<math> \sum^{0}_{k=n} 2^{k}</math>
 +
 +
<math> \sum^{-n}_{0} \frac{1}{2}^{k}, for n<0</math>
 +
<math> 0                            , for n>0</math>
 +
 +
<math> \sum^{-n}_{0} \frac{1}{2}^{k}</math>

Revision as of 13:25, 10 October 2008

Question 3.

  • An LTI system has unit impulse response h[n] =u[-n]. Compute the system's response to the input $ x[n] = 2^{n}u[-n]. $ Simplify your answer until all $ \sum $ signs disappear.)


Answer

$ y[n] = x[n] * h[n] , where * is convolution/, $

$ \sum^{\infty}_{k=-\infty} 2^{k}u[-k]u[-n+k] $

$ \sum^{0}_{k=-\infty} 2^{k}u[-n+k] $

$ \sum^{0}_{k=n} 2^{k} $

$ \sum^{-n}_{0} \frac{1}{2}^{k}, for n<0 $ $ 0 , for n>0 $

$ \sum^{-n}_{0} \frac{1}{2}^{k} $

Alumni Liaison

Ph.D. 2007, working on developing cool imaging technologies for digital cameras, camera phones, and video surveillance cameras.

Buyue Zhang