sampling theorem

sampling theorem

[′sam·pliŋ ‚thir·əm]
(communications)
The theorem that a signal that varies continuously with time is completely determined by its values at an infinite sequence of equally spaced times if the frequency of these sampling times is greater than twice the highest frequency component of the signal. Also known as Shannon's sampling theorem.
References in periodicals archive ?
No matter which propagation method used, the numerical computation enforces the sampling theorem for both the complex fields and propagators, this in order to guarantee the correct propagation of the optical field (Goodman, 2005; Li & Picart, 2012).
The Nyquist-Shannon Sampling Theorem of Fourier transform theory allows access to the range of values of variables below the Heisenberg Uncertainty Principle limit under sampling measurement conditions, as demonstrated by the Brillouin zones formulation of solid state physics [13] [14, see p.
Nyquist sampling theorem is widely accepted as a means of representing band-limited signals by their digital samples.
Therefore, to some extent, compressed sensing is considered as a sampling technology similar to Shannon's sampling theorem.
Huawei's FTN technology breaks the limit of the Nyquist sampling theorem, which defines a maximum transmission speed for a fixed channel bandwidth.
To digitize such UWB radar signal, a very high sampling rate is required according to Shannon-Nyquist sampling theorem [1], namely, the received signals must be sampled at twice their baseband bandwidth.
In this way, the sampling theorem is broken, cause the signal s(t) cannot correctly be sampled with the sampling frequency [f.
It is worthwhile to highlight yet another aspect of our geometric sampling method: Shannon's Sampling theorem relates to bandlimited signals, that are, necessarily, unbounded in time or in spatial domain.
The Nyquist sampling theorem differentiates samplers from digitizers.
The handbook's chapter titles include "Fourier Transforms in Probablility, Random Variables, and Stochastic Processes" and "Generalizations of the Sampling Theorem.
If the interested domain for the vibration signals is 0-200Hz, this means we have to used a sampling rate of minimum 400Hz, taking into account the Shannon sampling theorem.
Because a DDS device works with sampled data, designers must take into account the Nyquist sampling theorem.