How can the chirp-z transform be used in resampling?
in [DSP]
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From: quaste on 8 Feb 2007 10:08 Hi! I hope I'm not disturbing. ... > >"Andor" <an2or(a)mailcircuit.com> wrote in message >news:ce45f9ed.0403131537.34ec7122(a)posting.google.com... >> Matt Timmermans wrote: >> Although what you write is of course correct, this method doesn't >> strike me as very optimal in any sense. You have to take care of block >> effects when processing streams, it has high code complexity (FFT vs. >> FIR or polynomial interpolation), and fractional sample rate changes >> come at extremely high processing cost (as opposed to polyphase >> filtering approach). > >Yes, there are lots of situations in which that method of resampling is >inapplicable or impractical. > >> Isn't it the other way round: One uses FFTs to calculate chirp-z >> transforms? > >Both ways: You chirp-z to do a weird-length FFT. The chirp-z is based on >convolution, which you implement with a power-of-2-length FFT/IFFT. > I could be wrong, but isn't 'weird-length FFT' some contradiction? Isn't this a regular DFT, and a power-of-2-DFT is an FFT and the the chirp-z-transformation can be used to calculate some, let's call it, N-to-M DFT, with some N+M+1 < 2^k-FFT? >> I think the chirp-z transform has no real-world application in >> resampling. Parameters like quality and processing time are much >> better controlable with polyphase filtering or polynomial >> interpolation, at much lower code complexity. > >I would tend to think the same thing, except that I remember reading more >than one thread about FFT-based resampling in this very NG. > > > > best regards, Thomas
From: Robert Lietzmann on 28 Feb 2007 06:56 >Hi! > >I hope I'm not disturbing. >Maybe this is also interesting for you: If you want to know how to use CZT for auditory analysis of speech/music signals, please have a look to following article: An auditory spectral analysis model using the chirp z-transform Kates, J.; Acoustics, Speech, and Signal Processing [see also IEEE Transactions on Signal Processing], IEEE Transactions on Volume 31, Issue 1, Feb 1983 Page(s):148 - 156 Summary: In this paper we discuss a new signal-processing approach to implementing an auditory processing model. The model is based on auditory physiology and psychophysics; it uses constant-bandwidth analysis below 500 Hz and constant-Q analysis above 500 Hz..... Have a nice day, Robert > >> >>"Andor" <an2or(a)mailcircuit.com> wrote in message >>news:ce45f9ed.0403131537.34ec7122(a)posting.google.com... >>> Matt Timmermans wrote: >>> Although what you write is of course correct, this method doesn't >>> strike me as very optimal in any sense. You have to take care of block >>> effects when processing streams, it has high code complexity (FFT vs. >>> FIR or polynomial interpolation), and fractional sample rate changes >>> come at extremely high processing cost (as opposed to polyphase >>> filtering approach). >> >>Yes, there are lots of situations in which that method of resampling is >>inapplicable or impractical. >> >>> Isn't it the other way round: One uses FFTs to calculate chirp-z >>> transforms? >> >>Both ways: You chirp-z to do a weird-length FFT. The chirp-z is based >on >>convolution, which you implement with a power-of-2-length FFT/IFFT. >> > > > >I could be wrong, but isn't 'weird-length FFT' some contradiction? Isn't >this a regular DFT, and a power-of-2-DFT is an FFT and the the >chirp-z-transformation can be used to calculate some, let's call it, >N-to-M DFT, with some N+M+1 < 2^k-FFT? > > > >>> I think the chirp-z transform has no real-world application in >>> resampling. Parameters like quality and processing time are much >>> better controlable with polyphase filtering or polynomial >>> interpolation, at much lower code complexity. >> >>I would tend to think the same thing, except that I remember reading >more >>than one thread about FFT-based resampling in this very NG. >> >> >> >> > >best regards, >Thomas >
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