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Given <math>y[n] = x(nT)\,</math>, it is impossible to recontruct the signal back, since ther is loss of information when converting into a DT signal, but one can approximate it. | Given <math>y[n] = x(nT)\,</math>, it is impossible to recontruct the signal back, since ther is loss of information when converting into a DT signal, but one can approximate it. | ||
| − | [ | + | There is few types of interpolation. One of the common interpolation would be zero order interpolation, and for better approximation, Kth order interpolation can be used. |
| + | |||
| + | Examples of zero order interpolation can be found [http://en.wikipedia.org/wiki/Image:Zeroorderhold.impulseresponse.svg| here] and examples of first order interpolation can be found [http://en.wikipedia.org/wiki/First-order_hold| here]. | ||
Revision as of 11:14, 7 November 2008
Chapter 7
In chapter 7 we're going to learn how to represent a CT sgnal using samples.
Sampling
What is it? Sampling is a process of measuring a CT signal x(t) at some specific values of time t.
For example we can sample a continuous time signal x(t) at point t-1, t-2 and t-3. The sampled signal can represented by the formula $ y[n] = x(nT)\, $
The loss of information while sampling occurs depends on the signal and the frequency of the sample.
Given $ y[n] = x(nT)\, $, it is impossible to recontruct the signal back, since ther is loss of information when converting into a DT signal, but one can approximate it.
There is few types of interpolation. One of the common interpolation would be zero order interpolation, and for better approximation, Kth order interpolation can be used.
Examples of zero order interpolation can be found here and examples of first order interpolation can be found here.
