Discrete Fourier Transform

Description

In mathematics, the discrete Fourier transform (DFT) converts a finite sequence of equally-spaced samples of a function into a same-length sequence of equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency.

Parameters

$n$: length of the input data set

Table of Algorithms

Name	Year	Time	Space	Approximation Factor	Model	Reference
Naive algorithm	1965	$O(n^{2})$	$O({1})$	Exact	Deterministic
Cooley–Tukey algorithm	1965	$O(nlogn)$	$O(n)$?	Exact	Deterministic	Time
Rader–Brenner algorithm	1976	$O(nlogn)$	$O(n)$?	Exact	Deterministic	Time
Bruun's FFT algorithm	1978	$O(nlogn)$	$O(n)$?	Exact	Deterministic	Time
Yavne Split Radix FFT algorithm	1968	$O(nlogn)$	$O(n)$?	Exact	Deterministic	Time
Gentleman; Morven and Gordon Sande radix-4 algorithm	1966	$O(nlogn)$	$O(n)$?	Exact	Deterministic	Time
Bergland; Glenn radix-8 algorithm	1969	$O(nlogn)$	$O(n)$	Exact	Deterministic	Time & Space
Extended Split Radix FFT algorithm	2001	$O(nlogn)$	$O(n)$?	Exact	Deterministic	Time
Von zur Gathen-Gerhard additive FFT	1996	$O(n (logn)$^{2})	$O(n)$	Exact	Deterministic	Time & Space
Wang-Zhu-Cantor additive FFT	1988	$O(n(logn)$^{1.{58}5})	$O(n)$?	Exact	Deterministic	Time
Gao’s additive FFT	2010	$O(n logn loglogn)$	$O(n)$	Exact	Deterministic	Time & Space

Time Complexity graph

Space Complexity graph

Pareto Decades graph