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87 lines
3.5 KiB
Plaintext
87 lines
3.5 KiB
Plaintext
KISS FFT - A power-of-two 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 is:
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void * cfg = kiss_fft_alloc( nfft ,inverse_fft );
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while ...
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... // put kth sample in cx_buf_in_out[k].r and cx_buf_in_out[k].i
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kiss_fft( cfg , cx_buf_in_out );
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... // transformed
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free(cfg);
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Note: frequency-domain data is stored from dc to 2pi.
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so cx_buf_in_out[0] is the dc bin of the FFT
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and cx_buf_in_out[nfft/2] is the Nyquist bin
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Declarations are in "kiss_fft.h", along with a brief description of the
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two functions you'll need to use. Code definitions are in kiss_fft.c, along
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with sample usage code.
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The code can be easily recompiled to work with 16bit fixed point data,
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or various floating point types. 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 wanted to get some performance numbers against
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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 500 times as many lines of code as Kiss
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(and that's just the C code).
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2. It took me an embarrassingly long time to get FFT_BRANDX working.
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3. FFT_BRANDX is almost 3 times faster than Kiss
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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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PERFORMANCE:
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(on Athlon XP 2100+, with gcc 2.96, optimization O3, float data type)
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Kiss performed 1000 1024-pt ffts in 110 ms of cpu time (132ms real time).
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For comparison, it took md5sum 160ms cputime to process the same amount of data
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DO NOT:
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... use Kiss if you need the absolute fastest fft in the world
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... use Kiss if you need mixed radix FFTs
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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 uses a complex-only, frequency decimation, radix 2, in-place FFT. Bit reversed
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addressing is corrected as the last step in the transform. No scaling is done.
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LICENSE:
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BSD, see COPYING for details. Basically, "free to use, give credit where due, no guarantees"
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TODO:
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*) Add sample code for parallel ffts (stereo) packed into re,im components of time sequence.
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*) Add simple windowing function, e.g. Hamming : w(i)=.54-.46*cos(2pi*i/(n-1))
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*) Could mixed-radix FFTs be made simple enough to stand by the KISS principle?
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*) Make the fixed point scaling and bit shifts more easily configurable.
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*) Document/revisit the input/output fft scaling
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*) See if the fixed point code can be optimized a little without adding complexity.
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AUTHOR:
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Mark Borgerding
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Mark@Borgerding.net
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