Path: utzoo!attcan!uunet!seismo!ukma!tut.cis.ohio-state.edu!gem.mps.ohio-state.edu!apple!bionet!ames!ncar!tank!eecae!abaa!esker From: esker@abaa.uucp (Lawrence Esker) Newsgroups: comp.dsp Subject: Re: Adjust-Speed CD player?? Message-ID: <3441@abaa.UUCP> Date: 26 Sep 89 17:01:20 GMT References: <6028@jpl-devvax.JPL.NASA.GOV> <89255.105143P85025@BARILVM.BITNET><7767@microsoft.UUCP> <89264.171306P85025@BARILVM.BITNET> <7813@microsoft.UUCP> Reply-To: esker@abaa.UUCP (Lawrence Esker) Organization: Allen Bradley Lines: 45 In response to another article first, the terms FFT and real-time are oximoronic. To do an FFT in real time would mean computing the full FFT every sample period then scaling and inverse FFT in the same sample period. Maybe a super parallel processor could do it, if you have the money. The design of the FFT algoritm assumes you have access to all samples simulataneously to do the calculation. It is not geared toward one sample at a time calculation. To do this one must revert to the original DFT algorithm with a FIFO. This adds the effect on the current sample and removes the effects of (current - n) sample. In article <7813@microsoft.UUCP> brianw@microsoft.UUCP (Brian Willoughby) writes: >In article <89264.171306P85025@BARILVM.BITNET> P85025@BARILVM.BITNET (Doron Shikmoni) writes: >>Others suggested spectrum analysis and FFT to move from time domain >>to frequency domain and vice versa. [...] >> as I understand it ... this process should be made on >>a "quantum" at a time - it's not a continuous process. [...] >>Doron >You're right. The problem with FFTs is that they need a number of points >to work on. No matter how fast your 1000 point FFT is, you still have to >wait until another 1000 points are available. [...] >I read about a technique for a sliding window FFT. It was still an >N-point FFT (say 1000), but as each new sample was input the FFT is >recalculated. This method is also much faster for continuous data input, >because only the end points figure into the calculation. With a 1000 >point FFT example, the new transform is computed as a function only of >the newest point just added, and the oldest point which "falls out" of >the 1000 point buffer. [...] >I believe that this article was in the Electronic Design News. >Brian Willoughby Yes, the sliding-FFT looked like a great design invention until you studied it more closely and realized it was simply the original Discrete Fourier Transform (DFT) restated in a different way. Since the FFT is an algorithmic shortcut to the DFT, it made me chuckle to see the DFT used to perform the FFT, albeit under a new name of sliding-FFT. -- ---------- Lawrence W. Esker ---------- Modern Amish: Thou shalt not need any computer that is not IBM compatible. UseNet Path: __!mailrus!sharkey!itivax!abaa!esker == esker@abaa.UUCP