Howtosignalprocessing
- What is undersampling and oversampling in digital signal processing?
- What is oversampling in signal processing?
- What is the difference between undersampling and oversampling?
- What causes undersampling and oversampling?
What is undersampling and oversampling in digital signal processing?
Over-sampling implies having many more samples than the highest frequency of interest, and under-sampling implies we are down-converting the bandwidth of interest with a higher harmonic of the sampling clock (effectively).
What is oversampling in signal processing?
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.
What is the difference between undersampling and oversampling?
Oversampling methods duplicate or create new synthetic examples in the minority class, whereas undersampling methods delete or merge examples in the majority class. Both types of resampling can be effective when used in isolation, although can be more effective when both types of methods are used together.
What causes undersampling and oversampling?
Motivation for oversampling and undersampling. Both oversampling and undersampling involve introducing a bias to select more samples from one class than from another, to compensate for an imbalance that is either already present in the data, or likely to develop if a purely random sample were taken.
