In digital signal processing (DSP), a normalized frequency is a ratio of a variable frequency (f {\displaystyle f}) and a constant frequency associated with a system (such as a sampling rate, f s {\displaystyle f_{s}}). Some software applications require normalized inputs and produce normalized outputs, which can be re-scaled to physical units when necessary. Mathematical derivations are usually done in normalized units, relevant to a wide range of applications.

Examples of normalization

A typical choice of characteristic frequency is the sampling rate (f s {\displaystyle f_{s}}) that is used to create the digital signal from a continuous one. The normalized quantity, f ′ = f f s , {\displaystyle f'={\tfrac {f}{f_{s}}},} has the unit cycle per sample regardless of whether the original signal is a function of time or distance. For example, when f {\displaystyle f} is expressed in Hz (cycles per second), f s {\displaystyle f_{s}} is expressed in samples per second.

Some programs (such as MATLAB toolboxes) that design filters with real-valued coefficients prefer the Nyquist frequency ( f s / 2 ) {\displaystyle (f_{s}/2)} as the frequency reference, which changes the numeric range that represents frequencies of interest from [ 0 , 1 2 ] {\displaystyle \left[0,{\tfrac {1}{2}}\right]} cycle/sample to [ 0 , 1 ] {\displaystyle [0,1]} half-cycle/sample. Therefore, the normalized frequency unit is important when converting normalized results into physical units.

Example of plotting samples of a frequency distribution in the unit "bins", which are integer values. A scale factor of 0.7812 converts a bin number into the corresponding physical unit (hertz).

A common practice is to sample the frequency spectrum of the sampled data at frequency intervals of f s N , {\displaystyle {\tfrac {f_{s}}{N}},} for some arbitrary integer N {\displaystyle N} (see § Sampling the DTFT). The samples (sometimes called frequency bins) are numbered consecutively, corresponding to a frequency normalization by f s N . {\displaystyle {\tfrac {f_{s}}{N}}.} The normalized Nyquist frequency is N 2 {\displaystyle {\tfrac {N}{2}}} with the unit ⁠1/N⁠th cycle/sample.

Angular frequency, denoted by ω {\displaystyle \omega } and with the unit radians per second, can be similarly normalized. When ω {\displaystyle \omega } is normalized with reference to the sampling rate as ω ′ = ω f s , {\displaystyle \omega '={\tfrac {\omega }{f_{s}}},} 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:

QuantityNumeric rangeCalculationReverse
f ′ = f f s {\displaystyle f'={\tfrac {f}{f_{s}}}}[0, ⁠1/2⁠] cycle/sample1000 / 44100 = 0.02268f = f ′ ⋅ f s {\displaystyle f=f'\cdot f_{s}}
f ′ = f f s / 2 {\displaystyle f'={\tfrac {f}{f_{s}/2}}}[0, 1] half-cycle/sample1000 / 22050 = 0.04535f = f ′ ⋅ f s 2 {\displaystyle f=f'\cdot {\tfrac {f_{s}}{2}}}
f ′ = f f s / N {\displaystyle f'={\tfrac {f}{f_{s}/N}}}[0, ⁠N/2⁠] bins1000 × N / 44100 = 0.02268 Nf = f ′ ⋅ f s N {\displaystyle f=f'\cdot {\tfrac {f_{s}}{N}}}
ω ′ = ω f s {\displaystyle \omega '={\tfrac {\omega }{f_{s}}}}[0, π] radians/sample1000 × 2π / 44100 = 0.14250ω = ω ′ ⋅ f s {\displaystyle \omega =\omega '\cdot f_{s}}

See also