A look at the Nyquist sampling theorem. How to deal with aliasing by attenuating signals using low-pass filters (i.e., an antialiasing filter, or AAF). AAF requirements for different ADCs.

The central limit theorem is useful when analyzing large data sets because it allows one to assume that the sampling distribution of the mean will be normally distributed in most cases.

Posts Tagged: "Sampling Theorem" Operational Mathematics on a Processor is not an Abstract Idea ...

Central Limit Theorem, or CLT, is a statistical theory stating that as the size of a sample grows, the results tend to approximate a normal distribution of results. Read more here.

Sampling Theorem. According to the Sampling Theorem, an analog signal must be sampled at regular intervals over time and at twice the frequency of its highest-frequency component to be converted ...

The Nyquist sampling theorem has traditionally been applied to predict and mitigate aliasing. While effective in digital ...

The Central Limit Theorem for means: Central Limit Theorem for Means This Shiny app allows users to choose from several different population distributions, and to drag sliders to change the population ...