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KISS FFT - A mixed-radix Fast Fourier Transform based up on the principle,
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"Keep It Simple, Stupid."
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There are many great fft libraries already around. Kiss FFT is not trying
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to be better than any of them. It only attempts to be a reasonably efficient,
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moderately useful FFT that can use fixed or floating data types and can be
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incorporated into someone's C program in a few minutes with trivial licensing.
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USAGE:
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The basic usage for 1-d complex FFT is:
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#include "kiss_fft.h"
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kiss_fft_cfg cfg = kiss_fft_alloc( nfft ,is_inverse_fft ,0,0 );
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while ...
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... // put kth sample in cx_in[k].r and cx_in[k].i
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kiss_fft( cfg , cx_in , cx_out );
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... // transformed. DC is in cx_out[0].r and cx_out[0].i
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free(cfg);
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Note: frequency-domain data is stored from dc up to 2pi.
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so cx_out[0] is the dc bin of the FFT
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and cx_out[nfft/2] is the Nyquist bin (if exists)
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Declarations are in "kiss_fft.h", along with a brief description of the
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functions you'll need to use.
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Code definitions for 1d complex FFTs are in kiss_fft.c.
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You can do other cool stuff with the extras you'll find in tools/
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* multi-dimensional FFTs
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* real-optimized FFTs (returns the positive half-spectrum: (nfft/2+1) complex frequency bins)
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* fast convolution FIR filtering (not available for fixed point)
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* spectrum image creation
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The core fft and most tools/ code can be compiled to use float, double,
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Q15 short or Q31 samples. The default is float.
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BACKGROUND:
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I started coding this because I couldn't find a fixed point FFT that didn't
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use assembly code. I started with floating point numbers so I could get the
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theory straight before working on fixed point issues. In the end, I had a
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little bit of code that could be recompiled easily to do ffts with short, float
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or double (other types should be easy too).
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Once I got my FFT working, I was curious about the speed compared to
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a well respected and highly optimized fft library. I don't want to criticize
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this great library, so let's call it FFT_BRANDX.
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During this process, I learned:
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1. FFT_BRANDX has more than 100K lines of code. The core of kiss_fft is about 500 lines (cpx 1-d).
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2. It took me an embarrassingly long time to get FFT_BRANDX working.
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3. A simple program using FFT_BRANDX is 522KB. A similar program using kiss_fft is 18KB (without optimizing for size).
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4. FFT_BRANDX is roughly twice as fast as KISS FFT in default mode.
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It is wonderful that free, highly optimized libraries like FFT_BRANDX exist.
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But such libraries carry a huge burden of complexity necessary to extract every
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last bit of performance.
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Sometimes simpler is better, even if it's not better.
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FREQUENTLY ASKED QUESTIONS:
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Q: Can I use kissfft in a project with a ___ license?
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A: Yes. See LICENSE below.
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Q: Why don't I get the output I expect?
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A: The two most common causes of this are
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1) scaling : is there a constant multiplier between what you got and what you want?
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2) mixed build environment -- all code must be compiled with same preprocessor
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definitions for FIXED_POINT and kiss_fft_scalar
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Q: Will you write/debug my code for me?
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A: Probably not unless you pay me. I am happy to answer pointed and topical questions, but
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I may refer you to a book, a forum, or some other resource.
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PERFORMANCE:
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(on Athlon XP 2100+, with gcc 2.96, float data type)
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Kiss performed 10000 1024-pt cpx ffts in .63 s of cpu time.
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For comparison, it took md5sum twice as long to process the same amount of data.
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Transforming 5 minutes of CD quality audio takes less than a second (nfft=1024).
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DO NOT:
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... use Kiss if you need the Fastest Fourier Transform in the World
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... ask me to add features that will bloat the code
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UNDER THE HOOD:
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Kiss FFT uses a time decimation, mixed-radix, out-of-place FFT. If you give it an input buffer
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and output buffer that are the same, a temporary buffer will be created to hold the data.
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No static data is used. The core routines of kiss_fft are thread-safe (but not all of the tools directory).
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No scaling is done for the floating point version (for speed).
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Scaling is done both ways for the fixed-point version (for overflow prevention).
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Optimized butterflies are used for factors 2,3,4, and 5.
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The real (i.e. not complex) optimization code only works for even length ffts. It does two half-length
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FFTs in parallel (packed into real&imag), and then combines them via twiddling. The result is
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nfft/2+1 complex frequency bins from DC to Nyquist. If you don't know what this means, search the web.
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The fast convolution filtering uses the overlap-scrap method, slightly
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modified to put the scrap at the tail.
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LICENSE:
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Revised BSD License, see COPYING for verbiage.
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Basically, "free to use&change, give credit where due, no guarantees"
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Note this license is compatible with GPL at one end of the spectrum and closed, commercial software at
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A commercial license is available which removes the requirement for attribution. Contact me for details.
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TODO:
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*) Add real optimization for odd length FFTs
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*) Document/revisit the input/output fft scaling
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*) Make doc describing the overlap (tail) scrap fast convolution filtering in kiss_fastfir.c
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*) Test all the ./tools/ code with fixed point (kiss_fastfir.c doesn't work, maybe others)
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AUTHOR:
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Mark Borgerding
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Mark@Borgerding.net
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