Detection of Aliasing in Signals

We explain why an assumption of stationarity is suucient to give us the ability to detect aliasing in a temporally sampled signal process. We then deene a notion of stationarity that makes sense for single waveforms. (This is done without assuming that the waveform is a sample path of some underlying stochastic process.) We show how to use this concept to detect aliasing in sampled waveforms. The assumption that must be satissed to make this possible is shown to be fairly unrestrictive. We use simple harmonic signals to elucidate the method. Then we demonstrate the method's applicability to complex signals such as measurements from the Lorenz and RR ossler systems. Finally we suggest that the method might give us the ability to recover information about frequency components outside Nyquist band.