Teleki Electronics

Sampling Theory
A brief introduction to some sampling concepts.
The process of sampling is going to introduce a sinx/x rolloff in the passband, which is going to have to be corrected for, usually with a post filter that has its passband appropriately equalised. This originates from the Fourier transform of the sampling waveform (in time domain) being of a sinx/x nature in the frequency domain.

Consider an analogue signal with some sampling.

analogue signal and sampling

If the sampling waveform g(t) is of the form...

sampling waveform

multiply this by the analogue signal f(t), to give...

sampled analogue signal

ie s(t)=f(t).g(t)
Taking transforms, S(w)=F(w)*G(w) where * (in this case) means convolution.

The spectrum of g(t), ie G(w) is an infinite train of pulses (envelope has sinx/x shape).ie

spectrum of g(t)

Spectrum of f(t) is F(w).

spectrum of f(t)

If convolve the above two, then will get the total sampled data spectrum, ie S(w) which looks something like

result of convolution

If don't sample at a high enough rate, then will get overlap of components, ie aliasing. Two examples of this are the reverse rotating wagon wheel effect in old westerns and the banding seen around Helicopter blades.

The Nyquist theorem determines the relationship between the sampling frequency and the signal bandwidth, and states that the sampling frequency must be greater than twice the highest frequency component of the signal, for effective reconstruction to be possible. ie Fs>B*2 must be obayed, otherwise will get something like.

aliasing

If you're dealing with video signals, then some multiple of the colour subcarrier frequency is probably going to be used to sample each signal (YUV, RGB etc). This is usually as low as it can be, so its usually a good idea to have pre-alias filters used before any sampling is done. Reconstruction filters are used when the signal has been processed in some way and then needs to be used in an analogue form.

For broadcast Video, Elliptic function filters are normally used, due to the tight bandwidth constraints. However, these need to be amplitude/delay equalised to prevent signal distortion.

Audio signals are generally oversampled, so a linear phase filter can be used as both the anti-alias and reconstruction filter. In some situations it’s possible to get away with a simple RC circuit. Its even cheaper to have the filtering done somewhere on silicon.

Decimation/Interpolation
This is sample rate conversion, with decimation being a lowering of sample frequency, and interpolation being an increase in sample frequency, both of which are going to require low pass filtering to prevent aliasing. See the classic text by Abraham Peled and Bede Liu, "Digital Signal Processing" for further details.
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There's a certain amount of heavy maths involved in all this (degree level), which includes such things as Discrete Fourier Transforms, Convolution, Image Quantization etc, which if you like maths, you will absolutely enjoy !!.

Some functions can be done extremely fast, optically, without having to resort to using a DSP Processor, and its associated support circuitry. Some of this is still in the research stage, however.