Take your continuous signal and represent it with a Fourier series. Since the Fourier series is a linear decomposition into integer frequency sinusoids, the coefficients of the series tell you the amount of each frequency contained in the signal. The DFT gives you an approximation of these.
The coefficients of the Fourier series of a function are integrals. Approximate these integrals with a left Riemann sum. Integrals turn into sums ... sums turn into a linear system ... the linear system turns into a matrix ... bingobango there's the DFT matrix [3].
[1]: http://users.wpi.edu/~goulet/Matlab/overlap/efs.html
[2]: https://en.wikipedia.org/wiki/Riemann_sum#Left_Riemann_Sum
(I appreciate the post though, thanks)
I still don't understand how the FFT works though...
Yea. Maybe a loose analogy would be transforming from RGB to HSV space - the difference in how we can interpret the numbers in one versus the other is what's great.
It is trivial to coax the DTFT and DFT derivations if one understands the CTFT.
https://www.youtube.com/playlist?list=PL0INsTTU1k2UYO9Mck-i5...