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<math>x(t)\!</math> -----> x --------><math>x_p(t)\!</math>
 
<math>x(t)\!</math> -----> x --------><math>x_p(t)\!</math>
                          ^
+
                        ^
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+
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+
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                   <math>p(t) = \sum^{\infty}_{n = -\infty} \delta(t - nT)\!</math>
 
                   <math>p(t) = \sum^{\infty}_{n = -\infty} \delta(t - nT)\!</math>

Revision as of 12:44, 9 November 2008

Impulse-train Sampling

One type of sampling that satisfies the Sampling Theorem is called impulse-train sampling. This type of sampling is achieved by the use of a periodic impulse train multiplied by a continuous time signal, $ x(t)\! $. The periodic impulse train, $ p(t)\! $ is referred to as the sampling function, the period, $ T\! $, is referred to as the sampling period, and the fundamental frequency of $ p(t)\! $, $ \omega_s = \frac{2\pi}{T}\! $, is the sampling frequency. We define $ x_p(t)\! $ by the equation,

$ x_p(t) = x(t)p(t)\! $, where
$ p(t) = \sum^{\infty}_{n = -\infty} \delta(t - nT)\! $

Graphically, this equation looks as follows,

$ x(t)\! $ -----> x -------->$ x_p(t)\! $

                       ^
                       |
                       |
$ p(t) = \sum^{\infty}_{n = -\infty} \delta(t - nT)\! $

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