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