Fast, modern C++ DSP framework

Performance

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Highest possible performance is one of the main goals of the KFR framework.
Accurate benchmark measurements prove that KFR offers high speed implementations of the DSP algorithms

Our Fast Fourier Transform implementation is the fastest FFT according to measurements of the best available FFT libraries

FFT performance (double precision)

Biquad performance (single precision)

FFT benchmark source code

Examples

For more examples, check examples directory

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#include <kfr/all.hpp>

using namespace kfr;

...

univector<complex<float_type>, size> in  = sin(linspace(0.0, c_pi<float_type, 2> * 4.0, size));
univector<complex<float_type>, size> out = scalar(qnan);

// initialize fft
const dft_plan<float_type> dft(size);

// allocate work buffer for fft (if needed)
univector<u8> temp(dft.temp_size);

// perform forward fft
dft.execute(out, in, temp);

// scale output
out = out / size;

// get magnitude and convert to decibels
univector<float_type, size> dB = amp_to_dB(cabs(out));

println("max  = ", max(dB));
println("min  = ", min(dB));
println("mean = ", mean(dB));
println("rms  = ", rms(dB));