Revision as of 12:48, 9 November 2008 by Zcurosh (Talk)

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)\! $

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

By using linearity and the sifting property, $ x_p(t)\! $ can be represented as follows, $ x_p(t) = x(t)p(t)\! $ $ = x(t)\sum^{\infty}_{n = -\infty} \delta(t - nT)\! $ $ =\sum^{\infty}_{n = -\infty}x(t)\delta(t - nT)\! $

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

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