ShannonNyquistin

ShannonNyquistin is a term that combines two fundamental concepts in signal processing: the Shannon-Nyquist sampling theorem and the Nyquist frequency. The Shannon-Nyquist sampling theorem, often shortened to the sampling theorem, is a cornerstone of digital signal processing. It states that if a continuous-time signal has a bandwidth of B hertz, then it can be perfectly reconstructed from discrete samples taken at a sampling rate fs, provided that fs is greater than twice the highest frequency component of the signal. This minimum sampling rate is known as the Nyquist rate.

The Nyquist frequency, also sometimes called the folding frequency, is defined as half of the sampling rate. So, if a signal is sampled at a rate fs, the Nyquist frequency is fs/2. According to the sampling theorem, all frequency components of the original signal above the Nyquist frequency will be indistinguishable from lower frequencies when the signal is sampled. This phenomenon is called aliasing, and it leads to distortion in the reconstructed signal. Therefore, to avoid aliasing, the original signal must be filtered to remove any frequencies above the Nyquist frequency before sampling, or the sampling rate must be sufficiently high. The term ShannonNyquistin encapsulates the critical relationship between the sampling rate, the signal bandwidth, and the avoidance of aliasing, all derived from the principles established by Claude Shannon and Harry Nyquist.