Need FFT Code for Matlab (not built in)

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John
John 2013-3-15
评论： Marco Marcon 2024-4-28
Does anyone have FFT code for Matlab? I don't want to use the built-in Matlab function.
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John
John 2013-3-15
Okay I am looking for the O(n log n) algorithm for DFT then =)
Yasin Arafat Shuva
Yasin Arafat Shuva 2021-7-19
编辑：Rik 2021-7-19
clear variables
close all
%%Implementing the DFT in matrix notation
xn = [0 2 4 6 8]; % sequence of x(n)
N = length(xn); % The fundamental period of the DFT
n = 0:1:N-1; % row vector for n
k = 0:1:N-1; % row vecor for k
WN = exp(-1i*2*pi/N); % Wn factor
nk = n'*k; % creates a N by N matrix of nk values
WNnk = WN .^ nk; % DFT matrix
Xk = xn * WNnk; % row vector for DFT coefficients
disp('The DFT of x(n) is Xk = ');
disp(Xk)
magXk = abs(Xk); % The magnitude of the DFT
%%Implementing the inverse DFT (IDFT) in matrix notation
n = 0:1:N-1;
k = 0:1:N-1;
WN = exp(-1i*2*pi/N);
nk = n'*k;
WNnk = WN .^ (-nk); % IDFS matrix
x_hat = (Xk * WNnk)/N; % row vector for IDFS values
disp('and the IDFT of x(n) is x_hat(n) = ');
disp(real(x_hat))
% The input sequence, x(n)
subplot(3,1,1);
stem(k,xn,'linewidth',2);
xlabel('n');
ylabel('x(n)')
title('plot of the sequence x(n)')
grid
% The DFT
subplot(3,1,2);
stem(k,magXk,'linewidth',2,'color','r');
xlabel('k');
ylabel('Xk(k)')
title('DFT, Xk')
grid
% The IDFT
subplot(3,1,3);
stem(k,real(x_hat),'linewidth',2,'color','m');
xlabel('n');
ylabel('x(n)')
title('Plot of the inverse DFT, x_{hat}(n) = x(n)')
grid

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回答（4 个）

Youssef Khmou
Youssef Khmou 2013-3-15
hi John
Yes there are many versions of Discrete Fourier Transform :
% function z=Fast_Fourier_Transform(x,nfft)
%
% N=length(x);
% z=zeros(1,nfft);
% Sum=0;
% for k=1:nfft
% for jj=1:N
% Sum=Sum+x(jj)*exp(-2*pi*j*(jj-1)*(k-1)/nfft);
% end
% z(k)=Sum;
% Sum=0;% Reset
% end
% return
this is a part of the code , try my submission it contains more details :
http://www.mathworks.com/matlabcentral/fileexchange/40002-psd-power-spectral-density-and-amplitude-spectrum-with-adjusted-fft
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Abdullah Khan
Abdullah Khan 2013-11-28
编辑：Abdullah Khan 2013-11-28
This is also DFT
The complexity of the code is still N x N
because
% nfft=2^ceil(log2(N)) = nfft (on upper DTFT code )
or
% 2^ceil(log2(N))= N
Walter Roberson
Walter Roberson 2017-9-6
"FFT" stands for "Fast Fourier Transform", which is a particular algorithm to make Discrete Fourier Transform (DFT) more efficient.

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Tobias
Tobias 2014-2-11
编辑：Walter Roberson 2017-9-6
For anyone searching an educating matlab implementation, here is what I scribbled together just now:
function X = myFFT(x)
%only works if N = 2^k
N = numel(x);
xp = x(1:2:end);
xpp = x(2:2:end);
if N>=8
Xp = myFFT(xp);
Xpp = myFFT(xpp);
X = zeros(N,1);
Wn = exp(-1i*2*pi*((0:N/2-1)')/N);
tmp = Wn .* Xpp;
X = [(Xp + tmp);(Xp -tmp)];
else
switch N
case 2
X = [1 1;1 -1]*x;
case 4
X = [1 0 1 0; 0 1 0 -1i; 1 0 -1 0;0 1 0 1i]*[1 0 1 0;1 0 -1 0;0 1 0 1;0 1 0 -1]*x;
otherwise
error('N not correct.');
end
end
end
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Siddhant Sharma
Siddhant Sharma 2020-11-2
can anyone explain X equal to (Xp-tmp)?
Marco Marcon
Marco Marcon 2024-4-28
The total length of the final X will be N.
The first values will be given by + (remember that , and have length elements and both , are periodic of ); it can be written as for , where .
While the last values will be given by for .
Since we can get the second part of X(last values) as:
that is the reason for adding tmp in the first vector part and subtracting it in the second part.
For more details: Wikipedia: Cooley-Tukey algorithm

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Jan Afridi
Jan Afridi 2017-9-6
编辑：Jan Afridi 2017-11-6
I think I can answer your question. Check the given link may be it will help you. And if you found any error then please inform me... check the link Matlab code for Radix 2 fft
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Jan Suchánek
Jan Suchánek 2018-12-6
Hello i would like to ask you what had to be different if you would like to use it for harmonical function.
I tried to implement your solution but it was working only for random vectors but not for any type of harmonical.
i was using this for the harmonical function.
______________________
t2=0:1:255;
h1=sin(t2);
x=h1;
X11 = myFFT(x);
______________________
it gave me this error:
Error using *
Inner matrix dimensions must agree.
Error in myFFT (line 18)
X = [1 0 1 0; 0 1 0 -1i; 1 0 -1 0;0 1 0 1i]*[1 0 1 0;1
0 -1 0;0 1 0 1;0 1 0 -1]*x;
Error in myFFT (line 7)
Xp = myFFT(xp);
Error in myFFT (line 7)
Xp = myFFT(xp);
Error in myFFT (line 7)
Xp = myFFT(xp);
Error in myFFT (line 7)
Xp = myFFT(xp);
Error in myFFT (line 7)
Xp = myFFT(xp);
Error in myFFT (line 7)
Xp = myFFT(xp);
Error in ZBS_projekt (line 246)
X11 = myFFT(x);

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Ryan Black
Ryan Black 2019-3-11
编辑：Ryan Black 2020-8-26
Function I wrote that optimizes the DFT or iDFT for BOTH prime and composite signals...
https://www.mathworks.com/matlabcentral/fileexchange/70563-rader-s-mixed-radix-fft
The forward transform is triggered by -1 and takes the time-signal as a row vector:
[Y] = fftmodule(y,-1)
The inverse transform auto-normalizes by N, is triggered by 1 and takes the frequency-signal as a row vector:
[y] = fftmodule(Y,1)
Methodology:
The algorithm decimates to N's prime factorization following the branches and nodes of a factor tree. In formal literature this may be referred to as Mixed Radix FFT, but its really just recursive decimation of additive groups and this method is easily derivable via circular convolutions :)
At the prime tree level, algorithm either performs a naive DFT or if needed performs a single Rader's Algorithm Decomposition to (M-1), zero-pads to power-of-2, then proceeds to Rader's Convolution routine (not easy to derive). Finally it upsamples through the origianlly strucutured nodes and branches incorporating twiddle factors for the solution.

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