Evo par slika pa da vidi? ?ta je originalni a ?ta pomjereni spektar.
Plava boja označava spektar originalnog signala (početnog, analognog). Nakon odmjeravanja frekvencijom Fs, pojaviće se u spektru jo? jedna komponenta, identična kao i originalna ali pomjerena po frekventnoj osi sa centrom na frekvenciji odmjeravanja Fs (označeno sa zelenom linijom). Da bismo izdvojili originalni signal (plavi), potrebno je izvr?iti filtriranje pomoću low pass filtra koji će izdvojiti samo plavi spektar, odnosno koji će propustiti sve od 0 do krajnje frekvencije B (plavog spektra). Problem nastaje kad je prelazna oblast jako mala, to je oblast između najvi?e frekvencije originalnog signala (plavi) i najni?e frekvencije pomjerenog signala (zeleni) ili jo? gore kad dio ''zelenog'' spektra upadne u propusni opseg filtra zajedno sa ''plavim'' spektrom, kao na slici:
Da do preklapanja ne bi do?lo uzima se da frekvencija odmjeravanja mora biti najmanje 2 puta veća od najvi?e frekvencije u spektru ?to se vidi sa slike ( u tom slučaju je potreban idealni filtar sa prelaznom obla?ću jednakom 0 Hz) ili se uzima frekvencija odmjeravanja koja je malo veća od dvostruke najvi?e u spektru, da se obezbjedi dovoljna prelazna oblast za filtar.
Prelazna oblast koja se dobije sa 44.1 sampling rate-om je sasvim dovoljna za potpunu rekonstrukciju analognog signala samo je potreban skuplji filtar:
There are three main reasons for performing oversampling:
It aids in anti-aliasing because realizable analog anti-aliasing filters are very difficult to implement with the sharp cutoff necessary to maximize use of the available bandwidth without exceeding the Nyquist limit. By increasing the bandwidth of the sampled signal, the anti-aliasing filter has less complexity and can be made less expensively by relaxing the requirements of the filter at the cost of a faster sampler. Once sampled, the signal can be digitally filtered and downsampled to the desired sampling frequency. In modern integrated circuit technology, digital filters are much easier to implement than comparable analog filters of high order.
In practice, oversampling is implemented in order to achieve cheaper higher-resolution A/D and D/A conversion
Primjer:
For example, consider a signal with a bandwidth or highest frequency of fH = 100 Hz. The sampling theorem states that sampling frequency would have to be greater than 200 Hz. Sampling at 200 Hz would result in β = 1. Sampling at four times that rate (β = 4) would result in a sampling rate of 800 Hz. This gives the anti-aliasing filter a transition band of 600 Hz () instead of 0 Hz if the sampling frequency were at 200 Hz.
An anti-aliasing filter with a transition band of 600 Hz is much more realizable than that of 0 Hz (which would require a perfect filter). If the sampler went to eight times over then the transition band would increase to 1400 Hz, which means the anti-aliasing filter could be made cheaper due to a relaxation of the requirements.
After being sampled at 800 Hz, the signal could be digitally filtered to have a bandwidth of 400 Hz and then further downsampled to closer to 200 Hz.
Mislim da je sve jasno. Sorry zbog du?ine posta
