Fourier Transform Intro - Oscillation frequency vs Angular frequency Expression

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Fourier Transform

The Fourier transform is a generalization of the complex Fourier series in the limit as . Replace the discrete with the continuous while letting. Then change the sum to anintegral, and the equations become

			(1)
			(2)

Here,

			(3)
			(4)

is called the forward () Fourier transform, and

			(5)
			(6)

is called the inverse () Fourier transform. The notation is introduced in Trott (2004, p. xxxiv), and and are sometimes also used to denote the Fourier transform and inverse Fourier transform, respectively (Krantz 1999, p. 202).

Note that some authors (especially physicists) prefer to write the transform in terms of angular frequency instead of the oscillation frequency. However, this destroys the symmetry, resulting in the transform pair

			(7)
			(8)
			(9)
			(10)

To restore the symmetry of the transforms, the convention

			(11)
			(12)
			(13)
			(14)

is sometimes used (Mathews and Walker 1970, p. 102).

In general, the Fourier transform pair may be defined using two arbitrary constants and as

			(15)
			(16)

The Fourier transform of a function is implemented theWolfram Language asFourierTransform[f,x,k], and different choices of and can be used by passing the optionalFourierParameters-> a,b option. By default, theWolfram Language takesFourierParameters as. Unfortunately, a number of other conventions are in widespread use. For example, is used in modern physics, is used in pure mathematics and systems engineering, is used in probability theory for the computation of thecharacteristic function, is used in classical physics, and is used in signal processing. In this work, following Bracewell (1999, pp. 6-7),it is always assumed that and unless otherwise stated. This choice often results in greatly simplified transforms of common functions such as 1,, etc.

Since any function can be split up into even and odd portions and,

			(17)
			(18)

a Fourier transform can always be expressed in terms of the Fourier cosine transform and Fourier sine transform as

(19)

A function has a forward and inverse Fourier transform such that

(20)

provided that

1. exists.

2. There are a finite number of discontinuities.

3. The function has bounded variation. A sufficient weaker condition is fulfillment of the Lipschitz condition

(Ramirez 1985, p. 29). The smoother a function (i.e., the larger the number of continuousderivatives), the more compact its Fourier transform.

The Fourier transform is linear, since if and have Fourier transforms and, then

			(21)
			(22)

Therefore,

			(23)
			(24)

The Fourier transform is also symmetric since implies.

Let denote theconvolution, then the transforms of convolutions of functions have particularly nice transforms,

			(25)
			(26)
			(27)
			(28)

The first of these is derived as follows:

			(29)
			(30)
			(31)
			(32)

where .

There is also a somewhat surprising and extremely important relationship between theautocorrelation and the Fourier transform known as theWiener-Khinchin theorem. Let , and denote thecomplex conjugate of, then the Fourier transform of theabsolute square of is given by

(33)

The Fourier transform of a derivative of a function is simply related to the transform of the function itself. Consider

(34)

Now use integration by parts

(35)

with

			(36)
			(37)

and

			(38)
			(39)

then

(40)

The first term consists of an oscillating function times . But if the function is bounded so that

(41)

(as any physically significant signal must be), then the term vanishes, leaving

			(42)
			(43)

This process can be iterated for the thderivative to yield

(44)

The important modulation theorem of Fourier transforms allows to be expressed in terms of as follows,

			(45)
			(46)
			(47)
			(48)

Since the derivative of the Fourier transform is given by

(49)

it follows that

(50)

Iterating gives the general formula

			(51)
			(52)

The variance of a Fourier transform is

(53)

and it is true that

(54)

If has the Fourier transform, then the Fourier transform has the shift property

			(55)
			(56)

so has the Fourier transform

(57)

If has a Fourier transform, then the Fourier transform obeys a similarity theorem.

(58)

so has the Fourier transform

(59)

The "equivalent width" of a Fourier transform is

			(60)
			(61)

The "autocorrelation width" is

			(62)
			(63)

where denotes thecross-correlation of and and is thecomplex conjugate.

Any operation on which leaves itsarea unchanged leaves unchanged, since

(64)

The following table summarized some common Fourier transform pairs.

function
Fourier transform--1	1
Fourier transform--cosine
Fourier transform--delta function
Fourier transform--exponential function
Fourier transform--Gaussian
Fourier transform--Heaviside step function
Fourier transform--inverse function
Fourier transform--Lorentzian function
Fourier transform--ramp function
Fourier transform--sine

In two dimensions, the Fourier transform becomes

			(65)
			(66)

Similarly, the -dimensional Fourier transform can be defined for, by

			(67)
			(68)

SEE ALSO: Autocorrelation, Convolution, Discrete Fourier Transform, Fast Fourier Transform, Fourier Series, Fourier-Stieltjes Transform, Fourier Transform--1, Fourier Transform--Cosine, Fourier Transform--Delta Function, Fourier Transform--Exponential Function, Fourier Transform--Gaussian, Fourier Transform--Heaviside Step Function, Fourier Transform--Inverse Function, Fourier Transform--Lorentzian Function, Fourier Transform--Ramp Function, Fourier Transform--Rectangle Function, Fractional Fourier Transform, Hankel Transform, Hartley Transform, Integral Transform, Laplace Transform, Parseval's Theorem, Structure Factor, Wiener-Khinchin Theorem, Winograd Transform

REFERENCES:

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Blackman, R. B. and Tukey, J. W. The Measurement of Power Spectra, From the Point of View of Communications Engineering. New York: Dover, 1959.

Bracewell, R. The Fourier Transform and Its Applications, 3rd ed. New York: McGraw-Hill, 1999.

Brigham, E. O. The Fast Fourier Transform and Applications. Englewood Cliffs, NJ: Prentice Hall, 1988.

Folland, G. B. Real Analysis: Modern Techniques and their Applications, 2nd ed. New York: Wiley, 1999.

James, J. F. A Student's Guide to Fourier Transforms with Applications in Physics and Engineering. New York: Cambridge University Press, 1995.

Kammler, D. W. A First Course in Fourier Analysis. Upper Saddle River, NJ: Prentice Hall, 2000.

Körner, T. W. Fourier Analysis. Cambridge, England: Cambridge University Press, 1988.

Krantz, S. G. "The Fourier Transform." §15.2 in Handbook of Complex Variables. Boston, MA: Birkhäuser, pp. 202-212, 1999.

Mathews, J. and Walker, R. L. Mathematical Methods of Physics, 2nd ed. Reading, MA: W. A. Benjamin/Addison-Wesley, 1970.

Morrison, N. Introduction to Fourier Analysis. New York: Wiley, 1994.

Morse, P. M. and Feshbach, H. "Fourier Transforms." §4.8 in Methods of Theoretical Physics, Part I. New York: McGraw-Hill, pp. 453-471, 1953.

Oberhettinger, F. Fourier Transforms of Distributions and Their Inverses: A Collection of Tables. New York: Academic Press, 1973.

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Press, W. H.; Flannery, B. P.; Teukolsky, S. A.; and Vetterling, W. T.Numerical Recipes in FORTRAN: The Art of Scientific Computing, 2nd ed. Cambridge, England: Cambridge University Press, 1989.

Ramirez, R. W. The FFT: Fundamentals and Concepts. Englewood Cliffs, NJ: Prentice-Hall, 1985.

Sansone, G. "The Fourier Transform." §2.13 in Orthogonal Functions, rev. English ed. New York: Dover, pp. 158-168, 1991.

Sneddon, I. N. Fourier Transforms. New York: Dover, 1995.

Sogge, C. D. Fourier Integrals in Classical Analysis. New York: Cambridge University Press, 1993.

Spiegel, M. R. Theory and Problems of Fourier Analysis with Applications to Boundary Value Problems. New York: McGraw-Hill, 1974.

Stein, E. M. and Weiss, G. L. Introduction to Fourier Analysis on Euclidean Spaces. Princeton, NJ: Princeton University Press, 1971.

Strichartz, R. Fourier Transforms and Distribution Theory. Boca Raton, FL: CRC Press, 1993.

Titchmarsh, E. C. Introduction to the Theory of Fourier Integrals, 3rd ed. Oxford, England: Clarendon Press, 1948.

Tolstov, G. P. Fourier Series. New York: Dover, 1976.

Trott, M. TheMathematica GuideBook for Programming. New York: Springer-Verlag, 2004.http://www.mathematicaguidebooks.org/.

Walker, J. S. Fast Fourier Transforms, 2nd ed. Boca Raton, FL: CRC Press, 1996.

Weisstein, E. W. "Books about Fourier Transforms." http://www.ericweisstein.com/encyclopedias/books/FourierTransforms.html.

Referenced on Wolfram|Alpha: Fourier Transform