Aliasing can be avoided by means of applying low-pass filters or anti-aliasing filters before sampling. At a low sampling rate, the resulting signals do not represent the originals because of aliasing.Īliasing is the distortion of the original signal when it is reconstructed from samples that were taken at the sampling frequency below the Nyquist rate. On the other hand, if one samples a signal at a sample rate below its Nyquist rate, this is called undersampling. If a signal is sampled at a sampling frequency that is much higher than then the Nyquist rate, this is called oversampling. It is also called the folding frequency because of the symmetry of the resulting signal spectrum about the Nyquist frequency. The Nyquist frequency f n = 0.5 f s also called the Nyquist limit is half the sampling rate of a signal processor. According to this theorem, it is twice the maximum frequency of the signal being sampled. The Nyquist rate is the minimum sampling rate satisfying the Kotelnikov-Nyquist-Shannon sampling theorem for a given signal. For example, to reproduce sound in the human frequency range of 20 Hz to 20 kHz, the sampling frequency must be higher than 40 kHz. In sounds, the highest frequency is related to higher harmonics produced by various musical instruments. With images, the highest frequency is related to small structures or objects like, for example, grass or sand.
The Nyquist-Shannon sampling theorem states that to restore a signal, a sufficient sample rate must be greater than twice the highest frequency of the signal being sampled. The sampling interval or sampling period T s is the reciprocal of the sampling frequency: It is measured in the units of frequency - hertz. The sampling frequency, or sampling rate f s is the number of samples obtain in one second. A sample is a value of an analog signal at a point of time. Sampling is the technique used for recording analog information like audio signals or images by recording their snapshots at periodic intervals.