Editing Fourier analysis (section)

==Time–frequency transforms==
{{Further|Time–frequency analysis}}

In [[signal processing]] terms, a function (of time) is a representation of a signal with perfect ''time resolution'', but no frequency information, while the Fourier transform has perfect ''frequency resolution'', but no time information.

As alternatives to the Fourier transform, in [[time–frequency analysis]], one uses time–frequency transforms to represent signals in a form that has some time information and some frequency information – by the [[uncertainty principle]], there is a trade-off between these. These can be generalizations of the Fourier transform, such as the [[short-time Fourier transform]], the [[Gabor transform]] or [[fractional Fourier transform]] (FRFT), or can use different functions to represent signals, as in [[wavelet transforms]] and [[chirplet transform]]s, with the wavelet analog of the (continuous) Fourier transform being the [[continuous wavelet transform]].