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The image sampling frequency is the repetition rate of the sensor integration period. Since the integration period may be significantly shorter than the time between repetitions, the sampling frequency can be different from the inverse of the sample time: 50 Hz – PAL video; 60 / 1.001 Hz ~= 59.94 Hz – NTSC video
When is normalized with reference to the sampling rate as ′ =, the normalized Nyquist angular frequency is π radians/sample. The following table shows examples of normalized frequency for f = 1 {\displaystyle f=1} kHz , f s = 44100 {\displaystyle f_{s}=44100} samples/second (often denoted by 44.1 kHz ), and 4 normalization conventions:
Fig 1: Typical example of Nyquist frequency and rate. They are rarely equal, because that would require over-sampling by a factor of 2 (i.e. 4 times the bandwidth). In signal processing, the Nyquist rate, named after Harry Nyquist, is a value equal to twice the highest frequency of a given function or signal
For a given sampling rate (samples per second), the Nyquist frequency (cycles per second) is the frequency whose cycle-length (or period) is twice the interval between samples, thus 0.5 cycle/sample. For example, audio CDs have a sampling rate of 44100 samples/second. At 0.5 cycle/sample, the corresponding Nyquist frequency is 22050 cycles/second .
44,100 Hz, a customary rate used to sample audible frequencies is based on the limits of human hearing and the sampling theorem; Balian–Low theorem, a similar theoretical lower bound on sampling rates, but which applies to time–frequency transforms
A frequency distribution shows a summarized grouping of data divided into mutually exclusive classes and the number of occurrences in a class. It is a way of showing unorganized data notably to show results of an election, income of people for a certain region, sales of a product within a certain period, student loan amounts of graduates, etc.
Decimators can be used to reduce the sampling frequency, whereas interpolators can be used to increase it. Milic, Ljiljana (2009). Multirate Filtering for Digital Signal Processing. New York: Hershey. p. 35. ISBN 978-1-60566-178-0. Sampling rate conversion systems are used to change the sampling rate of a signal.
The sampling theory of Shannon can be generalized for the case of nonuniform samples, that is, samples not taken equally spaced in time. The Shannon sampling theory for non-uniform sampling states that a band-limited signal can be perfectly reconstructed from its samples if the average sampling rate satisfies the Nyquist condition. [1]