Signal Transforms

The idea of exploiting sampling randomization to achieve the capability of alias-free signal processing in a wide frequency range is attractive and often attracts attention. However, to achieve good results processing of nonuniformly represented signals must be carried out using special algorithms that take into account the specifics of this sampling approach. While this may seem to be obvious, it is less clear what criteria are required for evaluating the degree of matching the specifics of signal sampling and processing. This is not a trivial question. The following discussions explain to some extent why this is so. More about this is discussed in Chapter 18.

14.1 Problem of Matching Signal Processing to Sampling

These discussions will start by considering an example. Suppose that the mean power Px of a wideband signal x(t) component at frequency ωi that exceeds the mean sampling frequency ωs has to be estimated. The application of random sampling is clearly indicated. At first glance it seems that this task can be solved by estimating the Fourier coefficients ai and bi at the frequency ωi on the basis of the often applied formulae


The required estimate is then given as


Although these equations look like their conventional counterparts, they are in fact modified ...

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.