This code demonstrates the effect of aliasing by varying the frequency of a sinusoidal signal.
Aliasing concerns the miscalculation of the coefficients of low frequencies and the neglection of high frequency information in a signal, which happens when the sampling rate is too small (no enough sampling points) to capture the high frequency information. In order to avoid aliasing, the sampling rate should be bigger than the Nyquist frequency.
This code has three parts, sampling points will be indicated by blue circles:
(1) Illustration of signal processing before aliasing happens. The example signal (red curve) is in low frequency band so that the number of sampling points is sufficient.
(2) Illustration of the situation when aliasing happens. The number of sampling points is not enough to capture the high frequency signal (red curve). Instead, a low frequency signal (thick yellow line) will be erroneously attained.
(3) Illustration of the case when the sampling rate equals the Nyquist frequency. Correct signal will be calculated only when the sampling points sit at the peaks of the signal.