HW8: Difference between revisions

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[[image:FIR_filter_time.jpg]] [[Image:x_frequency3a.jpg]]
[[image:FIR_filter_time.jpg]] [[Image:x_frequency3a.jpg]]


and mathematically as: <math> g(t)= \sum_{-M}^{M}g(\frac{mT}{p})\delta (t-\frac{mT}{p}) </math> and <math> G(f) = \sum_{-M}^{M}g(mT)e^{-j2 \pi mT}</math>.


When we run the signal through this filter we multiply it mathematically in the time domain. In the frequency domain this will look like convolution. Because the oversampling rate is only 1 there will be no change on our signal in the time domain, but in the frequency we will see some changes.
[[Image:x_discrete_a.jpg]] [[Image:x_frequency3a.jpg]]

[[image:x_frequency4a.jpg]]

Revision as of 00:02, 25 November 2009

Problem Statement

Write a section describing how a CD player works with out oversampling but with digital filtering (1x oversampling)

Solution

CD players are used to play audio files and although these are limited we can look at any non periodic signal as periodic with an infinite period. We can represent this signal, x(t) as such in the time domain and X(f) in the frequency domain.

X continuous3.jpg X frequency1b.jpg

In order to take the signal and read it digitally we must sample it. This gives us data points creating a discrete function of time , where is and integer and is the period between samples. We use a frequency of 44 kHz as it is twice the frequency at which a human can hear (i.e. 2 x 22 kHz) -- that means, kHz. Mathematically sampling is represented by multiplying x(t) with the delta function which results in a convolution with X(f).

X discrete a.jpg X frequency2a.jpg

Represented as: and respectively.

This type of sampling can result in aliasing. This is prevented by oversampling represented on CD players and other media devices as Nx for N times oversampling. It is commonly seen at 8 or 16 and my latest player had it at 52. For this particular assignment we were asked to look at digital filtering but we can accommodate for any oversampling with the variable 'p'. We will use a FIR filter for this. It can be represented graphically as:

FIR filter time.jpg X frequency3a.jpg

and mathematically as: and .

When we run the signal through this filter we multiply it mathematically in the time domain. In the frequency domain this will look like convolution. Because the oversampling rate is only 1 there will be no change on our signal in the time domain, but in the frequency we will see some changes.

X frequency4a.jpg