# Fourier transform

(redirected from*Fourier transformation*)

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## Fourier transform

A mathematical operation by which a function expressed in terms of one variable,*x*, may be related to a function of a different variable,

*s*, in a manner that finds wide application in physics. The Fourier transform, F(

*s*), of the function f(

*x*) is given by

*s*) = f(

*x*) exp(–2πi

*xs*) d

*x*

*x*) = F(

*s*) exp(2πi

*xs*) d

*s*

The variables *x * and *s * are often called *Fourier pairs*. Many such pairs are useful, for example, time and frequency: the Fourier transform of an electrical oscillation in time gives the spectrum, or the power contained in it at different frequencies.

*The Great Soviet Encyclopedia*(1979). It might be outdated or ideologically biased.

## Fourier Transform

The Fourier transform of a function *f*(*x*) is the function *f*(*x*)

If *f*(*x*) is even, then *g*(*u*) takes the form

(the cosine transform), and if *f*(*x*) is odd, then *g*(*u*) takes the form

(the sine transform).

Formulas (1), (2), and (3) are invertible, that is, for even functions

for odd functions

and in general

To every operation on functions there corresponds an operation on their Fourier transforms that is frequently simpler than the operation on *f*(*x*). For example, the Fourier transform of *f*’(*x*) is *iug*(*u*). If

then *g*(*u*) = *g*_{1}(*u*)*g*_{2}(*u*). The Fourier transform of *f*(*x* + *a*) is *e ^{iua}g*(

*u*), and the Fourier transform of

*c*

_{1}

*f*

_{1}(

*x*) is

*c*

_{1}

*g*

_{1}(

*u*) +

*c*

_{2}

*g*

_{2}(

*u*).

If

exists, then the integrals in formulas (1) and (6) converge in the mean (*see*CONVERGENCE) and

(Plancherel’s theorem). Formula (8) is the extension of Parse-val’s formula to Fourier transforms (*see*PARSEVAL EQUALITY). In physical terms, formula (8) states that the energy of a certain vibration is the sum of the energies of its harmonic components. The map *F*:*f*(*x*) → *g*(*u*) is a unitary operator in the Hubert space of square integrable functions *f*(*x*), – ∞ < *x* < ∞. This operator can also be represented in the form

Under certain conditions on *f*(*x*) we have the Poisson formula

which is of use in the theory of theta functions.

If the function *f*(*x*) decreases sufficiently rapidly, then it is also possible to define its Fourier transform for certain complex values *u* = *v* + *iw*. For example, if

exists, then the Fourier transform is defined for |*w*| < *a*. There is a close connection between the complex Fourier transform and the two-sided Laplace transform

The Fourier transform operator can be extended to classes of functions larger than the class of integrable functions; for example, if (1 + |*x*|)^{–1}*f*(*x*) is integrable, then the Fourier transform of *f*(*x*) is given by formula (9). The operator can even be extended to certain classes of generalized functions (generalized functions with a slow rate of growth).

There exist generalizations of the Fourier transform. One of them makes use of various special funtions, such as Bessel functions. This generalization is fully developed in the representation theory of continuous groups. Another generalization is the Fourier-Stieltjes transform, which is frequently applied in, for example, probability theory; it is defined for every bounded nondecreasing function ϕ(*x*) by means of the Stieltjes integral

and is called the characteristic function of the distribution ϕ. According to the Bochner-Khinchin theorem, for *g*(*u*) to be representable by (10) it is necessary and sufficient that

for every choice of *u*_{1}, . . ., *u _{n}*, ξ

_{1}, . . ., ξ

_{n}.

First introduced in heat conduction theory, the Fourier transform has many applications in mathematics. For example, it is used in the solution of differential, difference, and integral equations and in the theory of special functions. Many branches of theoretical physics also make use of the transform. Thus, the Fourier transform provides the standard apparatus for quantum field theory and is widely applied in the method of Green’s functions for nonequilibrium problems of quantum mechanics and thermodynamics and in scattering theory.

### REFERENCES

Sneddon, I.*Preobrazovanie Fur’e*. Moscow, 1955. (Translated from English.)

Vladimirov, V. S.

*Obobshchennye funktsii v matematicheskoi fizike*. Moscow, 1976.

## Fourier transform

[‚fu̇r·ē‚ā ′tranz‚fȯrm]*t*), the function

*F*(

*x*) equal to 1/√(2π) times the integral over

*t*from -∞ to ∞ of ƒ(

*t*) exp (

*itx*).

## Fourier transform

(mathematics)Computers generally rely on the version known as discrete Fourier transform.

Named after J. B. Joseph Fourier (1768 -- 1830).

See also wavelet, discrete cosine transform.

**foldoc.org**)

## FFT

(**F**ast

**F**ourier

**T**ransform) A computer algorithm used in digital signal processing (DSP) to modify, filter and decode digital audio, video and images. FFTs commonly change the time domain into the frequency domain.

**Myriad Recognition Uses**

FFTs are widely used in voice recognition and myriad other pattern recognition applications. For example, noise-cancelling headphones use FFT to turn unwanted sounds into simple waves so that inverse signals can be generated to cancel them. FFTs are used to sharpen edges and create effects in static images and are widely used to turn a number series into sine waves and graphs.

**Fast DFT Processing**

The FFT quickly performs a discrete Fourier transform (DFT), which is the practical application of Fourier transforms. Developed by Jean Baptiste Joseph Fourier in the early 19th century, the Fourier equations were invented to transform one complex function into another. One of Fourier's primary goals was to predict the rate of heat transfer based on temperature, mass and proximity. In practice, the terms FFT, DFT and Fourier transform are used synonymously. See DSP.

An FFT Transform |
---|

A Fourier transform was used to chart the power levels at different frequencies from the half second of digital samples (top). |

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