The math behind digital sampling and filtering is fascinating, complex, and full of arcane terms like Nyquist frequency. But I'm barely a good enough mathematician to understand it, let alone try to ...

Suppose you take a few measurements of a time-varying signal. Let’s say for concreteness that you have a microcontroller that reads some voltage 100 times per second. Collecting a bunch of data points ...

Previous articles in Planet Analog make mention of the “aliasing effect.” Most EEs agree in the importance of the aliasing effect as a noise source and take for granted that anti-aliasing filters are ...

Sampling a signal causes the original signal spectrum (blue) to create sum (purple) and difference (red) frequencies around the sampling frequency, fS. When the difference signals fall into the ...

In An Approximation to the Aliasing Effect, Part 1: The Origin I revisited some basic concepts about the aliasing effect, though I did it from a more visual than theoretical perspective. This second ...

In an October column about undersampling, I explained how a data acquisition system could use aliasing to move signals within bandwidth x into a lower-frequency portion of the spectrum. That column ...

The relationship between a signal’s constituent frequencies and the sampling rate used to quantize them is fundamental. As shown in Figure 1, sampling a signal that has a given spectrum creates a ...