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Method 2 will work in more general cases, e.g. where the ratio of sample rates is not rational, or two real-time streams must be accommodated, or the sample rates are time-varying. See decimation and upsampling for further information on sample-rate conversion filter design/implementation.
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 .
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
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
The samples (sometimes called frequency bins) are numbered consecutively, corresponding to a frequency normalization by . [2]: p.56 eq.(16) [3] The normalized Nyquist frequency is with the unit 1 / N th cycle/sample. Angular frequency, denoted by and with the unit radians per second, can be similarly normalized.
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 lower value of n will also lead to a useful sampling rate. For example, using n = 4, the FM band spectrum fits easily between 1.5 and 2.0 times the sampling rate, for a sampling rate near 56 MHz (multiples of the Nyquist frequency being 28, 56, 84, 112, etc.). See the illustrations at the right.
The sampling theorem states that sampling frequency would have to be greater than 200 Hz. Sampling at four times that rate requires a sampling frequency of 800 Hz. This gives the anti-aliasing filter a transition band of 300 Hz ((f s /2) − B = (800 Hz/2) − 100 Hz = 300 Hz) instead of 0 Hz if the sampling frequency was 200 Hz. Achieving an ...