Nyquist rate
From Wikipedia, the free encyclopedia
- Not to be confused with Nyquist frequency.
In signal processing, the Nyquist rate is two times the bandwidth—but this concept has two rather different meanings: as a lower bound for the sample rate for alias-free signal sampling, and as an upper bound for the signaling rate across a bandwidth-limited channel such as a telegraph line.
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[edit] Nyquist rate sampling
The Nyquist rate is the minimum sampling rate required to avoid aliasing when sampling a continuous signal. In other words, the Nyquist rate is the minimum sampling rate required to allow unambiguous reconstruction of a bandlimited continuous signal from its samples. If the input signal is real and bandlimited, the Nyquist rate is simply twice the highest frequency contained within the signal. In other words, the Nyquist rate is equal to the two-sided bandwidth of the signal.
where 
is the highest frequency component contained in the signal.
To avoid aliasing, the sampling rate must exceed the Nyquist rate:
[edit] Signaling at the Nyquist rate
Long before Harry Nyquist had his name associated with sampling, the term Nyquist rate was used differently, with a meaning closer to what Nyquist actually studied. Quoting Harold S. Black's 1953 book Modulation Theory, in the section Nyquist Interval of the opening chapter Historical Background:
- "If the essential frequency range is limited to B cycles per second, 2B was given by Nyquist as the maximum number of code elements per second that could be unambiguously resolved, assuming the peak interference is less half a quantum step. This rate is generally referred to as signaling at the Nyquist rate and 1/(2B) has been termed a Nyquist interval." (bold added for emphasis; italics as in the original)
According to the OED, this is may be the origin of the term Nyquist rate.
Nyquist's famous 1928 paper was a study on how many pulses (code elements) could be transmitted per second, and recovered, through a channel of limited bandwidth. Signaling at the Nyquist rate meant putting as many code pulses through a telegraph channel as its bandwidth would allow. Shannon used Nyquist's approach when he proved the sampling theorem in 1948, but Nyquist did not work on sampling per se.
Black's later chapter on "The Sampling Principle" does give Nyquist some of the credit for some relevant math:
- "Nyquist (1928) pointed out that, if the function is substantially limited to the time interval T, 2BT values are sufficient to specify the function, basing his conclusions on a Fourier series representation of the function over the time interval T."
[edit] See also
- Harry Nyquist
- Nyquist–Shannon sampling theorem
- Sampling frequency
- Nyquist frequency — The Nyquist rate is defined differently from the Nyquist frequency, which is the frequency equal to half the sampling rate of a sampling system, and is not a property of a signal.
- Nyquist ISI criterion
[edit] Reference
- Black, H. S., Modulation Theory, v. 65, 1953, cited in OED
| Digital Signal Processing |
|---|
| Theory — Nyquist–Shannon sampling theorem, estimation theory, detection theory |
| Sub-fields — audio signal processing | control engineering | digital image processing | speech processing | statistical signal processing |
| Techniques — Discrete Fourier transform (DFT) | Discrete-time Fourier transform (DTFT) | bilinear transform | Z-transform, advanced Z-transform |
| Sampling — oversampling | undersampling | downsampling | upsampling | aliasing | anti-aliasing filter | sampling rate | Nyquist rate/frequency |
