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Revision as of 01:35, 12 January 2023 editQuondum (talk | contribs)Extended confirmed users36,927 edits Alternative normalizations: minor unit rearrangement (we should not be splitting out units from the input quantities)← Previous edit Revision as of 13:50, 12 January 2023 edit undoQuondum (talk | contribs)Extended confirmed users36,927 edits Alternative normalizations: ce statementNext edit →
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== Alternative normalizations == == Alternative normalizations ==


Some programs (such as ] toolboxes) that design filters with real-valued coefficients prefer a characteristic frequency of {{math|''f''<sub>s</sub>/2}} (the ]), which expands the upper limit of useful frequencies from {{math|1/2}} to {{math|1.}} Some programs (such as ] toolboxes) that design filters with real-valued coefficients prefer the the ] as a characteristic frequency ({{math|''f''<sub>s</sub>/2}}), which replaces the numeric range that represents frequencies of interest from {{math|}} to {{math|}}.


], denoted by {{math|''ω''}} and with the unit ], can be similarly normalized. When {{math|''ω''}} is normalized with reference to the sampling rate, the resulting unit is radian per sample. The normalized Nyquist angular frequency is ''π''&nbsp;radians/sample. ], denoted by {{math|''ω''}} and with the unit ], can be similarly normalized. When {{math|''ω''}} is normalized with reference to the sampling rate, the resulting unit is radian per sample. The normalized Nyquist angular frequency is ''π''&nbsp;radians/sample.

Revision as of 13:50, 12 January 2023

Frequency divided by a characteristic frequency

In digital signal processing (DSP), a normalized frequency (f) is a quantity that is equal to the ratio of a frequency and a characteristic frequency of a system.

A typical choice of characteristic frequency is the sampling rate (fs) that is used to create the digital signal from a continuous one. The normalized quantity, f′ = f / fs, typically has the unit cycle per sample regardless of whether the original signal is a function of time, space, or something else. For example, when f is expressed in Hz (cycles per second), fs is expressed in samples per second.

This allows us to present concepts that are universal to all sample rates in a way that is independent of the sample rate. Such a concept is a digital filter design whose bandwidth is specified not in hertz, but as a percentage of the sample rate of the data passing through it. Formulas expressed in terms of fs (or Ts ≡ 1 / fs) are readily converted to normalized frequency by setting those parameters to 1. The inverse operation is usually accomplished by replacing instances of the frequency parameter, f, with f / fs or f Ts.

Alternative normalizations

Some programs (such as MATLAB toolboxes) that design filters with real-valued coefficients prefer the the Nyquist frequency as a characteristic frequency (fs/2), which replaces the numeric range that represents frequencies of interest from to .

Angular frequency, denoted by ω and with the unit radian per second, can be similarly normalized. When ω is normalized with reference to the sampling rate, the resulting unit is radian per sample. The normalized Nyquist angular frequency is π radians/sample.

The following table shows examples of normalized frequencies for a 1 kHz signal, a sampling rate fs = 44,100 samples/second (often denoted by 44.1 kHz), and 3 normalization options.

Quantity Numeric range Computation Value
f′ = f / fs     1000 cycles/second / 44100 samples/second 0.02268 cycle/sample
ν′ = f / (fs/2) = 2f / fs     (1000 cycles/second × 2 half-cycles/cycle) / 44100 samples/second 0.04535 half-cycle/sample
ω′ = ω / fs     (1000 cycles/second × 2π radians/cycle) / 44100 samples/second 0.14250 radian/sample

See also

Notes and citations

  1. Carlson, Gordon E. (1992). Signal and Linear System Analysis. Boston, MA: ©Houghton Mifflin Co. pp. 469, 490. ISBN 8170232384.
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