Periodic Versus Randomized Sampling

Signal sampling, in general, is a well-investigated and described process. However, there are also some essential issues of sampling that are not usually given much attention. The dependence of aliasing on conditions of signal sample value taking and on the specifics of signal processing might be mentioned as examples. That is understandable. Indeed, in the case of traditional periodic sampling, the aliasing effect is not acceptable at all. Sampling then has to be performed in such a way that the sampled signals are not distorted by aliasing. Under these conditions, studying the impact of various sampling and processing conditions on the aliasing effect does not make sense. The situation is completely different when randomization of sampling is considered as a means of making the application of fully digital signal processing possible in a much wider frequency range. The processes accompanying aliasing need to be understood really well as the impact of various sampling conditions on frequency overlapping plays a very important role. To randomize signal sampling properly, it is essential to know how variations of the periodic sampling conditions, including variations of the periodic sampling phase, affect the characteristics of the obtained sampled signals.

Some issues of sampling, essential both for sampling and processing of sampled signals, are considered in this chapter. Variable phase periodic sampling processes are discussed, in addition, ...

Get Digital Alias-free Signal Processing now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.