Writing a Discrete Fourier Transform program

Question

I would like to write a DFT program using FFT. This is actually used for very large matrix-vector multiplication (10^8 * 10^8), which is simplified to a vector-to-vector convolution, and further reduced to a Discrete Fourier Transform.

May I ask whether DFT is accurate? Because the matrix has all discrete binary elements, and the multiplication process would not tolerate any non-zero error probability in result. However from the things I currently learnt about DFT it seems to be an approximation algorithm?

Also, may I ask roughly how long would the code be? i.e. would this be something I could start from scratch and compose in C++ in perhaps one or two hundred lines? Cause actually this is for a paper...and all I need is that the complexity analyis is O(nlogn) and the coefficient in front of it doesn't really matter :) So the simplest implementation would be best. (Although I did see some packages like kissfft and FFTW, but they are very lengthy and probably an overkill for my purpose...)

Answer 1

A canonical radix-2 FFT can be written in less than 200 lines of C++. The average numerical error is roughly proportional to O(log N), so you will need to use a large enough numeric type and data scale factor to account for this.

Answer 2

You can compute numerically stable convolutions using the Number Theoretic transform. It uses unique integer sequences to compute the discrete Fourier transform over integer fields/rings. The only caveat is that the signal needs to be integer valued.

It is implementation is roughly the same size as the FFT, but a little faster. You can find my implementation of it at finitetransform.sourceforge.net as the NTTW sub-library. The APFloat library might be more relevant to your needs as they do multiplication of large numbers using convolutions.