8 - 1x oversampling: Difference between revisions

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New page: Write a section on the Wiki about how a CD player works with no oversampling, but digital filtering (1x oversampling)<br><br> First we sample the data at <math> f_s = \frac{1}{T} </math> ...
 
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and <math> \frac{1}{T}\sum_{n=-\infty}^\infty X(f - \frac{n}{T})</math> in the frequency domain. <br><br>
and <math> \frac{1}{T}\sum_{n=-\infty}^\infty X(f - \frac{n}{T})</math> in the frequency domain. <br><br>


Now that we have the data in the computer we want to convolve it with another impulse function <math> \sum_{m=-M}^M h(\frac{mT}{n})\delta(t-\frac{mT}{n})</math> in the time domain. This is where more that 1x oversampling would occur replace n for nx oversampling, but in our case we use n = 1. Doing this convolution we can also shape our frequency when you convolve in time it multiplies in frequency. So we pick a frequency function <math> \sum_{m=-M}^M h(\frac{mT}{n})e^{-j2\pi fm\frac{T}{n}} </math> to multiply by so our frequency won't overlap later and help compensate for losses in the D/A converter.
Now that we have the data in the computer we want to convolve it with another impulse function <math> \sum_{m=-M}^M h(\frac{mT}{n})\delta(t-\frac{mT}{n})</math> in the time domain. This is where more that 1x oversampling would occur replace n for nx oversampling, but in our case we use n = 1. Doing this convolution we can also shape our frequency when you convolve in time it multiplies in frequency. So we pick a frequency function <math> \sum_{m=-M}^M h(\frac{mT}{n})e^{-j2\pi fm\frac{T}{n}} </math> to multiply by so our frequency won't overlap later and help compensate for losses in the D/A converter. Example the frequency function is. <br><br>
<math> \sum_{m=-M}^M h(\frac{mT}{n})e^{-j2\pi fm\frac{T}{n}} \Longrightarrow </math> [[Image:x_frequency3a.jpg]]<br>
 
Now doing the convolution/multiplication yields. <br>
The time domain stays the same with [[Image:x_discrete_a.jpg]]<br>
But frequency <br> [[Image:x_frequency2a.jpg|thumb|none|upright = 1|]]x[[Image:x_frequency3a.jpg|thumb|none|upright = 1|]]=[[Image:x_frequency4a.jpg|thumb|none|upright = 1|]]<br><br>






[[Image:x_discrete_a.jpg]]<br>


[[Image:x_frequency3a.jpg]]<br>
[[Image:x_frequency3a.jpg]]<br>

Revision as of 18:51, 8 November 2009

Write a section on the Wiki about how a CD player works with no oversampling, but digital filtering (1x oversampling)

First we sample the data at fs=1T to get the data in digital form and when you use the impulse function in time the frequency repeats forever as shown


                                 Sample fs=1T


Where the impulse function with respect to time = n=x(nt)δ(tnT)
and 1Tn=X(fnT) in the frequency domain.

Now that we have the data in the computer we want to convolve it with another impulse function m=MMh(mTn)δ(tmTn) in the time domain. This is where more that 1x oversampling would occur replace n for nx oversampling, but in our case we use n = 1. Doing this convolution we can also shape our frequency when you convolve in time it multiplies in frequency. So we pick a frequency function m=MMh(mTn)ej2πfmTn to multiply by so our frequency won't overlap later and help compensate for losses in the D/A converter. Example the frequency function is.

m=MMh(mTn)ej2πfmTn

Now doing the convolution/multiplication yields.
The time domain stays the same with

But frequency

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x

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