Alternatives
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: the magnitude of the Fourier transform at a point is how much frequency content there is, but location is only given by phase (argument of the Fourier transform at a point), and standing waves are not localized in time – a sine wave continues out to infinity, without decaying. This limits the usefulness of the Fourier transform for analyzing signals that are localized in time, notably transients, or any signal of finite extent.
As alternatives to the Fourier transform, in time-frequency analysis, one uses time-frequency transforms or time-frequency distributions 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 or fractional Fourier transform, or other functions to represent signals, as in wavelet transforms and chirplet transforms, with the wavelet analog of the (continuous) Fourier transform being the continuous wavelet transform. (Boashash 2003).
Read more about this topic: Fourier Transform
Famous quotes containing the word alternatives:
“The last alternatives they face
Of face, without the life to save,
Being from all salvation weaned
A stag charged both at heel and head:
Who would come back is turned a fiend
Instructed by the fiery dead.”
—Allen Tate (1899–1979)
“The literal alternatives to [abortion] are suicide, motherhood, and, some would add, madness. Consequently, there is some confusion, discomfort, and cynicism greeting efforts to “find” or “emphasize” or “identify” alternatives to abortion.”
—Connie J. Downey (b. 1934)
“Clearly, society has a tremendous stake in insisting on a woman’s natural fitness for the career of mother: the alternatives are all too expensive.”
—Ann Oakley (b. 1944)