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<math> \omega_c \rightarrow \omega_m < \omega_c < \omega_s - \omega_m</math>.
 
<math> \omega_c \rightarrow \omega_m < \omega_c < \omega_s - \omega_m</math>.
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This process can be easily shown in the frequency domain graphically. An example is below.
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[[Image:Freq_Domain_ECE301Fall2008mboutin.png|Graph]]

Revision as of 19:42, 10 November 2008

Proving the Sampling Theorem

The sampling can be represented by "Impulse-train Sampling."

$ x_p(t) = ? $ $ x_p(t) = x(t)p(t) $ $ x_p(t) = x(t)\sum_{n=-\infty}^{\infty} \delta(t-nT) $

We can recover $ x(t) $ from $ x_p(t) $ as follows:

$ x_p(t) \rightarrow H(\omega) \rightarrow x_r(t) $

Where $ H(\omega) $ is a filter with gain equal to the period of the signal and a cutoff frequency of $ \omega_c $.

$ \omega_c \rightarrow \omega_m < \omega_c < \omega_s - \omega_m $.

This process can be easily shown in the frequency domain graphically. An example is below.

Graph

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

Buyue Zhang