An Introduction to the Sampling Theorem

The consequences of sampling a signal at a rate below its highest frequency component results in a phenomenon known as aliasing . This concept results in a frequency mistakenly taking on the identity of an entirely different frequency when recovered. In an attempt to clarify this, envision the ideal sampler of Figure 1(a) , with a sample period of T shown in (b), sampling the waveform f(t) as pictured in (c). The sampled data points of f’(t) are shown in (d) and can be defined as the sample set of the continuous function f(t). Note in Figure 1(e) that another frequency component, a’(t), can be found that has the same sample set of data points as f’(t) in (d). Because of this it is difficult to determine which frequency a’(t), is truly being observed. This effect is similar to that observed in western movies when watching the TL/H/5620–1