The Nyquist–Shannon sampling theorem is a fundamental theory providing the condition on the sampling frequency of a bandwidth-limited continuous-time signal in order to be able to reconstruct it perfectly from its discrete-time (sampled) version. It states that the sampling frequency must be at least two times the highest frequency of the continuous-time signal spectrum.
June 23, 2017—Ghassane Aniba
What Is a Signal?
A signal is a time/space-varying function that includes some useful information. Most signals are continuous-time ones, and hence cannot be either stored or transmitted over realistic limited-data storage (or band-limited propagation space) due to an infinite number of points to be processed.
Such signals could be of different sources or types, such as audio, or any real-life physical measure or parameter retrieved by sensors (temperature, humidity, speed, ...).
An example of a continuous-time* signal—the mean temperature during 2016 in Rabat, Morocco:
In order to process real-life signals either to store or transmit them, we need to perform a sampling process on them, making them discrete time signals.