Howtosignalprocessing
- Why do we oversample signals?
- What happens when you oversample a signal?
- Is oversampling a signal bad?
- Why do we oversample and decimate?
Why do we oversample signals?
Oversampling is capable of improving resolution and signal-to-noise ratio, and can be helpful in avoiding aliasing and phase distortion by relaxing anti-aliasing filter performance requirements.
What happens when you oversample a signal?
Oversampling reduces or completely gets rid of 3 forms of potential distortion a signal can have: aliasing, clipping, and quantization distortion. Although these forms of distortion are often mild and difficult to consciously hear, they're often noticed when using a lot of processing or pushing a processor harder.
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.
Why do we oversample and decimate?
Oversampling and Decimation is commonly used in ADC to improve the resolution. This technique requires large number of samples, these extra samples can be achieved by oversampling the input signal. Here oversampling refers to sampling the signal by a factor greater than the bare minimum Nyquist rate.
