aliasointiilmiö

Aliasointiilmiö, often translated as aliasing phenomenon or simply aliasing, is an effect that occurs when a signal is sampled at too low a rate. When a continuous signal is converted into a discrete signal through sampling, the sampling frequency must be at least twice the highest frequency present in the signal for the original signal to be accurately reconstructed. This is known as the Nyquist-Shannon sampling theorem.

If the sampling rate is less than twice the highest frequency, higher frequencies in the original signal can be misinterpreted as lower frequencies in the sampled signal. This distortion is the aliasointiilmiö. The aliased frequencies appear as new, spurious frequencies that were not present in the original signal.

In digital signal processing, aliasointiilmiö can lead to significant errors and misinterpretations of data. For example, in audio, it can cause high-pitched sounds to be perceived as lower-pitched ones. In image processing, it can manifest as jagged edges or moiré patterns.

To prevent aliasointiilmiö, anti-aliasing filters are often used. These are low-pass filters that are applied to the signal before sampling. The filter removes or attenuates frequencies above half the sampling rate, ensuring that no frequencies exist that could cause aliasing. Digital signal processing techniques can also be employed to mitigate or correct aliasing after it has occurred, although prevention is generally preferred for optimal signal fidelity.