<html><head></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">Hi Lucas,<div><br></div><div>Sorry for the late reply. But since one doesn't really learn the true nature of the FFT in 5 days, I think this may still be helpful.</div><div><br></div><div>My favorite resources for learning & teaching about FFT are:</div><div>- Julius Smith's online tutorial: <a href="https://ccrma.stanford.edu/~jos/mdft/">https://ccrma.stanford.edu/~jos/mdft/</a></div><div>- Ken Steigglitz's book: <a href="http://www.amazon.com/Digital-Signal-Processing-Primer-Applications/dp/0805316841/ref=sr_1_1?ie=UTF8&s=books&qid=1295230522&sr=8-1">http://www.amazon.com/Digital-Signal-Processing-Primer-Applications/dp/0805316841/ref=sr_1_1?ie=UTF8&s=books&qid=1295230522&sr=8-1</a> This book will teach you not just about FFT, but about musical signal processing in general -- it's well worth the money.</div><div><br></div><div>Both are written with music in mind. </div><div><br></div><div>For a much higher-level overview, you can see my FFT "cheat sheet" here: <a href="http://www.cs.princeton.edu/~fiebrink/314/2010/week8/FFT_handout_2010.pdf">http://www.cs.princeton.edu/~fiebrink/314/2010/week8/FFT_handout_2010.pdf</a></div><div>along with code examples from that day of class here <a href="http://www.cs.princeton.edu/~fiebrink/314/2010/week8/">http://www.cs.princeton.edu/~fiebrink/314/2010/week8/</a></div><div>and scribe notes (written by a student) here <a href="http://www.cs.princeton.edu/~fiebrink/314/2010/week8/scribe_Mia.pdf">http://www.cs.princeton.edu/~fiebrink/314/2010/week8/scribe_Mia.pdf</a></div><div><br></div><div>Best,</div><div>Rebecca</div><div><br><div><div>On 2011-01-11, at 9:00 AM, <a href="mailto:chuck-users-request@lists.cs.Princeton.EDU">chuck-users-request@lists.cs.Princeton.EDU</a> wrote:</div><blockquote type="cite"><div><font class="Apple-style-span" color="#000000"><br></font>Date: Tue, 11 Jan 2011 09:27:42 -0200<br>From: Lucas Zawacki <<a href="mailto:lfzawacki@gmail.com">lfzawacki@gmail.com</a>><br>To: ChucK Users Mailing List <<a href="mailto:chuck-users@lists.cs.princeton.edu">chuck-users@lists.cs.princeton.edu</a>><br>Subject: [chuck-users] Using Fourier Transform<br>Message-ID:<br><span class="Apple-tab-span" style="white-space:pre"> </span><<a href="mailto:AANLkTi=vBnKCqQoKaii3Bq1jscdnqqLd1j21PUkBsPPi@mail.gmail.com">AANLkTi=vBnKCqQoKaii3Bq1jscdnqqLd1j21PUkBsPPi@mail.gmail.com</a>><br>Content-Type: text/plain; charset=ISO-8859-1<br><br>Sup guys. This is not much of a ChucK question but here goes...<br><br>I have some free time now to experiment with ChucK and I dug up some<br>old emails from the list. There's one talking about analysing the<br>frequency of a given signal and the short answer was to use the FFT.<br><br>I decided I would try this aproach in order to receive input from my<br>guitar, match the frequency being played and then issue a MIDI event<br>to another synthesizing app. The problem is that I have a very<br>abstract understanding of the FFT (I've used it before to do simple<br>image processing). It does makes sense to me, e.g I can visualize in<br>my mind what the FFT of a simple sound wave would look like, but I<br>wasn't competent enough to extract the absolute pitch data that I<br>wanted.<br><br>Anyway can someone elaborate a little more on the topic of frequency<br>analisys or maybe point me to a good tutorial?<br><br>I think I'll start with the wikipedia article on the Fourier Transform<br>and see where it gets me...<br><br>-- <br><a href="http://www.twitter.com/lfzawacki">http://www.twitter.com/lfzawacki</a><br>http://www.linesocode.wordpress.com<br><br><br>------------------------------<br><br>_______________________________________________<br>chuck-users mailing list<br>chuck-users@lists.cs.princeton.edu<br>https://lists.cs.princeton.edu/mailman/listinfo/chuck-users<br><br><br>End of chuck-users Digest, Vol 66, Issue 9<br>******************************************<br></div></blockquote></div><br></div></body></html>