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    In mathematics, in the area of harmonic analysis, the fractional Fourier transform (FRFT) is a linear transformation generalizing the Fourier transform. It can be thought of as the Fourier transform to the n-th power where n need not be an integer — thus, it can transform a function to an intermediate domain between time and frequency. Its applications range from filter design and signal analysis to phase retrieval and pattern recognition.
    The FRFT can be used to define fractional convolution, correlation, and other operations, and can also be further generalized into the linear canonical transformation (LCT). An early definition of the FRFT was given by Namias (1980), but it was not widely recognized until it was independently reinvented around 1993 by several groups of researchers (Almeida, 1994).

    A completely different meaning for "fractional Fourier transform" was introduced by Bailey and Swartztrauber (1991) as essentially another name for a z-transform, and in particular for the case that corresponds to a discrete Fourier transform shifted by a fractional amount in frequency space (multiplying the input by a linear chirp) and evaluating at at fractional set of frequency points (e.g. considering only a small portion of the spectrum). (Such transforms can be evaluated efficiently by Bluestein's FFT algorithm.) This terminology has fallen out of use in most of the technical literature, however, in preference to the FRFT. The remainder of this article describes the FRFT.

    See also the chirplet transform for a related generalization of the Fourier transform.


        Fractional Fourier transform
            Definition
            See also

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    Definition

    If the continuous Fourier transform of a function f(t) is denoted by mathcal(f), then mathcal^2(f)=mathcal(mathcal(f)), and in general mathcal^(f)=mathcal(mathcal^n(f)); similarly, mathcal^(F) denotes the n-th power of the inverse transform mathcal^(F) of F(omega). The FRFT further extends this definition to handle non-integer powers n=2alpha/pi for any real alpha, denoted by mathcal_alpha(f) and having the properties:

    mathcal_alpha(f) = mathcal^(f)


    when n=2alpha/pi is an integer, and:

    mathcal_(f) = mathcal_alpha(mathcal_eta(f)) = mathcal_eta(mathcal_alpha(f)).


    More specifically, mathcal_alpha(f) is given by the equation:

    mathcal_alpha(f)(omega) =

    sqrt
    e^
    int_^infty
    e^
    f(t) dt


    Note that, for alpha=pi/2, this becomes precisely the definition of the continuous Fourier transform, and for alpha=-pi/2 it is the definition of the inverse continuous Fourier transform.

    If alpha is an integer multiple of pi, then the cotangent and cosecant functions above diverge. However, this can be handled by taking the limit, and leads to a Dirac delta function in the integrand. More easily, since mathcal^2(f)=f(-t), mathcal_alpha(f) must be simply f(t) or f(-t) for alpha an even or odd multiple of pi, respectively.

    There also exist related fractional generalizations of similar transforms such as the discrete Fourier transform.

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    See also

    Other time-frequency transforms:

     
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    Scientus.org Dictionary (Yet Another Wiki) RC : 1.39
    This article is licensed under the GNU Free Documentation License [copyleft]. It uses material from the Wikipedia article "Fractional Fourier transform". link