Oversampling a signal

In signal processing, oversampling is the process of sampling a signal at a sampling frequency significantly higher than the Nyquist rate. Theoretically, a bandwidth-limited signal can be perfectly reconstructed if sampled at the Nyquist rate or above it.

1. What is the purpose of oversampling?
2. Is oversampling a signal bad?
3. What happens when oversampling?
4. What is oversampling and undersampling in signals and systems?

What is the purpose of oversampling?

Oversampling is used to study small groups, not bias poll results.

Is oversampling a signal bad?

Oversampling compresses the signal bandwidth to a smaller part of the frequency axis, and can make subtle filters harder to design and implement because of this. You may, for example, need a filter that drops like a rock instead of something with a smaller slope, so you may need higher orders.

What happens when oversampling?

Oversampling is the practice of selecting respondents so that some groups make up a larger share of the survey sample than they do in the population. Oversampling small groups can be difficult and costly, but it allows polls to shed light on groups that would otherwise be too small to report on.

What is oversampling and undersampling in signals and systems?

The undersampling technique removes this stage of down conversion and 70 MHz is directly given to ADC. Oversampling increases the cost of the ADC. By using the above example of 70-MHz IF with 20-MHz , the sampling rate for the undersampling case is 56 MSPS whereas for the oversampling case it is 200 MSPS.