The applet demonstrates graphically how an undersampled sinusoidal signal appears as though it has a lower "alias" frequency.
According to the sampling theorem, a sinusoidal signal (or component of a more complex signal) can be correctly reconstructed from values sampled at discrete, uniform intervals as long as the signal frequency is less than half the sampling frequency. Any component of a sampled signal with a frequency above this limit, often referred to as the folding frequency, is subject to aliasing.
The applet is based on a fixed sampling rate of 8000 samples per second (one sample every 0.125 milliseconds). The folding frequency is thus half of 8000 Hz or 4000 Hz.
The input signal frequency, in Hz, is typed into the text box. When you click the Plot button, with Input signal checked, the input signal is plotted against time. The Grid checkbox toggles on and off vertical gridlines indicating the instants at which the signal is sampled. The Sample points, representing the sampled values of the input signal, can also be toggled. Finally, the Alias frequency checkbox (visible only when the input signal frequency is above the 4000 Hz folding frequency) controls the plotting of a sinusoidal signal at the alias frequency - in other words, the input signal as it appears after the sampling process.
See the Java 1.1 version page for an explanation of how to use the applet to illustrate how aliasing arises.
Download source code (zip archive)
FFT Spectrum Analyser applet: 1.02 version | 1.1 version