Hi to all, I've been writing an application in JAVA that uses the Fourier Transform, and performs several operations, such as the convolution. The convolution is being processed in the time domain, so when signals lenths are big (i.e. 1000 values or more), it takes very long to process the convolution. So the best way to do this is by working in the frequency domain. Does anybody know a Java fft code that works for signals whose lengths can be different than power or 2???? Thanks in advance!

# Java fft (not power of 2)

Started by ●August 11, 2008

Reply by ●August 11, 20082008-08-11

On Aug 11, 12:46 am, "amyanes" <amya...@gmail.com> wrote:> Hi to all, > > I've been writing an application in JAVA that uses the Fourier Transform, > and performs several operations, such as the convolution. > > The convolution is being processed in the time domain, so when signals > lenths are big (i.e. 1000 values or more), it takes very long to process > the convolution. > > So the best way to do this is by working in the frequency domain. > > Does anybody know a Java fft code that works for signals whose lengths can > be different than power or 2???? > > Thanks in advance!Google returned source code for this in 0.22 seconds. Were you hoping for quicker response time here? John

Reply by ●August 11, 20082008-08-11

>Google returned source code for this in 0.22 seconds. Were you hoping >for quicker response time here? > >John >I would really appreciatte it if you posted the link here. I've been looking for a long time (maybe not doing it right), and only find algorithms that work to transform signals that have lengths that correspond to a power of 2. I need to be able to transform any array of any size. Is it what you found??? Thanks

Reply by ●August 11, 20082008-08-11

On Aug 11, 10:38 am, "amyanes" <amya...@gmail.com> wrote:> >Google returned source code for this in 0.22 seconds. Were you hoping > >for quicker response time here? > > >John > > I would really appreciatte it if you posted the link here. I've been > looking for a long time (maybe not doing it right), and only find > algorithms that work to transform signals that have lengths that correspond > to a power of 2. I need to be able to transform any array of any size. Is > it what you found??? ThanksYou can visit www.google.com/codesearch and enter "mixed radix fft lang:java" into the search box. Here's a snapshot from one of the results with LGPL license: package jnt.FFT; /** * Computes FFT's of complex, single precision data of arbitrary length n. This * class uses the Mixed Radix method; it has special methods to handle factors * 2, 3, 4, 5, 6 and 7, as well as a general factor. * <P> * This method appears to be faster than the Radix2 method, when both methods * apply, but requires extra storage (which ComplexDoubleFFT_Mixed manages * itself). * * <P> * See {@link ComplexFloatFFT ComplexFloatFFT}for details of data layout. * * @author Bruce R. Miller bruce.miller@nist.gov * @author Contribution of the National Institute of Standards and Technology, * @author not subject to copyright. * @author Derived from GSL (Gnu Scientific Library) * @author GSL's FFT Code by Brian Gough bjg@vvv.lanl.gov * @author Since GSL is released under * @author <H HREF="http://www.gnu.org/copyleft/gpl.html">GPL </A>, * @author this package must also be. */

Reply by ●August 11, 20082008-08-11

You can always use an FFT that is a power of 2. Say you want to convolve a signal that is 78 points by one that is 1500 points. Pad each signal with zeros to make them each 2048 points long. FFT convolution of these 2048 point long signals will give you an answer that is 2048 points long, with the first 78+1500-1 = 1577 points being the convolution, and the remaining 471 points being zero. Here's a link. Regards, Steve http://www.dspguide.com/ch18.htm

Reply by ●August 11, 20082008-08-11

Steve Smith wrote:> You can always use an FFT that is a power of 2. Say you want to convolve a > signal that is 78 points by one that is 1500 points. Pad each signal with > zeros to make them each 2048 points long. FFT convolution of these 2048 > point long signals will give you an answer that is 2048 points long, with > the first 78+1500-1 = 1577 points being the convolution, and the remaining > 471 points being zero. Here's a link. > Regards, > Steve > > http://www.dspguide.com/ch18.htmCircular convolution of linear? Jerry -- Engineering is the art of making what you want from things you can get. �����������������������������������������������������������������������

Reply by ●August 12, 20082008-08-12