This is an implementation of the 'Nonstationary Gabor transform' (Inversible Constant Q Transform) in C. It supports forward and backward transform of the whole or streamed signal. It currently only does complex to complex transforms with double floating point precision.
The library consists of the files nsgt.h and nsgt.c. To make deployment as easy as possible, the project contains a sln file for Visual Studio 2015 and cmakelists.txt for CLion to compile and execute the added examples.
Usage of the library should be relatively straight forwards, and basic examples are found in the examples folder.
Executing the examples will yield something similar to this:
Test full nsgt Initialization in 393.626 ms Forward in 28.885ms, Backwards in 26.427ms, Error: -152.032db Test nsgt stream (sliCQ) Initialization in 132.662 ms Forward in 5.999ms, Backwards in 4.990ms, Forward in 5.374ms, Backwards in 4.906ms, Error: -152.613db Forward in 5.254ms, Backwards in 4.995ms, Error: -152.779db Forward in 5.255ms, Backwards in 4.871ms, Error: -153.877db Forward in 5.717ms, Backwards in 4.921ms, Error: -152.243db Forward in 5.305ms, Backwards in 5.449ms, Error: -152.238db Forward in 5.392ms, Backwards in 5.009ms, Error: -152.481db Forward in 5.422ms, Backwards in 4.861ms, Error: -152.391db Forward in 5.220ms, Backwards in 4.856ms, Error: -150.750db
The papers and original Matlab implementation can be found here: http://www.univie.ac.at/nonstatgab/
A Python implementation can be found here: https://github.com/grrrr/nsgt
Roadmap and contributing
The following items need to be addressed:
- apart from double floating point precision, the library needs to support float and long double precision.
- real-to-complex forward and complex-to-real backwards tranforms needs to be implemented to save memory and time
- other fft libraries should be supported, one of them possibly be included to get rid of the dependencies
- other frequency scalings should be supported (currently only octave)
- support fftw wisdom and serialization
If you want to contribute, please fork this repository and make a pull request with your changes. It is greatly appreciated.
note that FFTW is licensed with GPLv2