Prof Brad Osgood has some excellent Fourier transform lectures on iTunesU
(The Fourier Transform and its Applications).
In particular, there's a few lectures (~lectures 10-14 I think) on distributions and Schwartz functions that help show how Fourier transforms of sines, exponentials, deltas, ... can be better justified. Suprisingly (to me after having seen and given up trying to understand Functional analysis), the basics required for application are not actually all that difficult, mostly requiring a change in approach, and an extra level of indirection.
Some lecture notes to go with the lectures can be found here:
I am experimenting with non uniform sampling, I applied Fast Fourier transform on the non uniform sampling in matlab it has given me some results. I cant understand how FFT runs on non uniform sampling. What i am getting after applying FFT on Non uniform samples is what....is it a errorfull value if yes then why
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