In signal processing, sampling is the process of converting a [[continuous-time signal]] into a [[discrete-time signal]] by taking samples of the continuous-time signal at regular intervals. The resulting discrete-time signal can be stored, processed, and transmitted more efficiently than the original continuous-time signal. The rate at which the samples are taken is known as the sampling rate or [[sampling frequency]]. The Nyquist-Shannon sampling theorem states that to accurately reconstruct a continuous-time signal from its samples, the sampling rate should be greater than twice the highest frequency component in the original signal. If the [[discrete-time signal]] $x(n)$ is the result of sampling the [[continuous-time signal]] $x_c(t)$, then: $ x(n) = x_c(nT), \forall n \in \mathbb{Z} $ where $x_c(t)$ is a function of the variable $t \in \mathbb{R}$ and $T$ is the [[sampling period]]. ![[amost1.svg|600]]