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I think you're being downvoted because anyone who is interested in DSP already knows about Fourier transforms, they're fundamental and quite well known. Frankly, I'm surprised to find that they're new to so many HN readers.


Fundamental if you ever finished a CS degree. Shamefully, the Wikipedia articles (German and English) aren't really good, and I dropped out of university before FFT was a topic.

Lots of HN readers are self-thaught hackers or come from non-theoretic backgrounds... so they likely won't have had a good explanation of it. (Speaking of which, the circle analogy is truly awesome - but how does it work in code?!)


And not necessarily if you did finish a CS degree. I was never taught about them, apparently only electronics/signal processing folks were at my uni.


I'll just mention http://www.dspguide.com/ as a really fantastic resource - a free book aimed at scientists and engineers but so well written as to be easily accessible to the interested lay person.

A lot of the math-related articles on Wikipedia are terrible. When you look at the page for the Math project the FAQ basically says 'it's an encyclopaedia, not a textbook, go write on the talk page of individual articles.' The project managers seem hyper-defensive about it, in constrast to the comprehensive and inclusive approach of many other fields. The Wikibooks project is not much better (so far).

I find the Wolfram Mathematica pages more accessible for dealing with new concepts.


It's more of an electronic engineering thing than CS


In fairness, it's more of an everything thing. You won't get far in any science without hitting a Fourier transform somewhere!


Yes, and in music too. When I worked as intern at IRCAM FFT was a big deal, and was the only part of the code we weren't allowed to checkout.




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