BLUESTEIN'S FFT ALGORITHM

Bluestein's FFT algorithm (1968), also called the chirp-z algorithm (1969), is a fast Fourier transform (FFT) algorithm that computes the discrete Fourier transform (DFT) of arbitrary sizes (including prime sizes) by re-expressing the DFT as a convolution. (The other algorithm for FFTs of prime sizes, Rader's algorithm, also works by rewriting the DFT as a convolution.)

Recall that the DFT is defined by the formula

If we replace the product jk in the exponent by the identity jk = -(j-k)²/2 + j²/2 + k²/2, we thus obtain:

This summation is precisely a convolution of the two sequences a_k and b_k of length n (k = 0,...,n-1) defined by:

with the output of the convolution multiplied by n phase factors b_j^*.

This convolution, in turn, can be performed with a pair of FFTs (plus the pre-computed FFT of b_k) via the convolution theorem. Although this may seem circular, the key point is that these FFTs need not be of the same length n. Rather, a convolution can always be computed exactly by zero-padding it to any size greater than or equal to 2n-1. In particular, one can pad to a power of two or some other highly composite size, for which the FFT can be efficiently computed by e.g. the Cooley-Tukey algorithm in O(n log n) time. Thus, Bluestein's algorithm provides an O(n log n) way to compute prime-size DFTs, albeit several times slower than the Cooley-Tukey algorithm for composite sizes.

Chirp z-Transforms

In fact, Bluestein's algorithm can be used to compute more general transforms than the DFT, called chirp z-transforms (Rabiner, 1969); this is any transform of the form:

for an arbitrary complex number α, and for differing numbers n and m of inputs and outputs. Given Bluestein's algorithm, such a transform can be used, for example, to obtain a more finely spaced interpolation of some portion of the spectrum (although the frequency resolution is still limited by the total sampling time), enhance arbitrary poles in transfer-function analyses, etcetera.

References:

• Leo I. Bluestein, "A linear filtering approach to the computation of the discrete Fourier transform," Northeast Electronics Research and Engineering Meeting Record 10, 218-219 (1968).
• Lawrence R. Rabiner, Ronald W. Schafer, and Charles M. Rader, "The chirp z-transform algorithm and its application," Bell Syst. Tech. J. 48, 1249-1292 (1969).
• D. H. Bailey and P. N. Swarztrauber, "The fractional Fourier transform and applications," SIAM Review 33, 389-404 (1991). [Note that this terminology for the chirp z-transform is nonstandard: a fractional Fourier transform conventionally refers to an entirely different, continuous transform.]