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In categorization tasks with two options and m cues—also known as features or attributes—available for making such a decision, an FFT is defined as follows: A fast-and-frugal tree is a classification or a decision tree that has m+1 exits, with one exit for each of the first m −1 cues and two exits for the last cue.
The Bailey's FFT (also known as a 4-step FFT) is a high-performance algorithm for computing the fast Fourier transform (FFT). This variation of the Cooley–Tukey FFT algorithm was originally designed for systems with hierarchical memory common in modern computers (and was the first FFT algorithm in this so called "out of core" class).
In bioinformatics, MAFFT (multiple alignment using fast Fourier transform) is a program used to create multiple sequence alignments of amino acid or nucleotide sequences. . Published in 2002, the first version used an algorithm based on progressive alignment, in which the sequences were clustered with the help of the fast Fourier transfo
where "FFT" denotes the fast Fourier transform, and f is the spatial frequency spans from 0 to N/2 – 1. The proposed FFT-based imaging approach is diagnostic technology to ensure a long life and stable to culture arts. This is a simple, cheap which can be used in museums without affecting their daily use.
Once the transform has been broken up into subtransforms of sufficiently small sizes, FFTW uses hard-coded unrolled FFTs for these small sizes that were produced (at compile time, not at run time) by code generation; these routines use a variety of algorithms including Cooley–Tukey variants, Rader's algorithm, and prime-factor FFT algorithms.
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As with the Cooley–Tukey FFT algorithm, the two dimensional vector-radix FFT is derived by decomposing the regular 2-D DFT into sums of smaller DFT's multiplied by "twiddle" factors. A decimation-in-time ( DIT ) algorithm means the decomposition is based on time domain x {\displaystyle x} , see more in Cooley–Tukey FFT algorithm .
This category is for fast Fourier transform (FFT) algorithms, i.e. algorithms to compute the discrete Fourier transform (DFT) in O(N log N) time (or better, for approximate algorithms), where is the number of discrete points.