Blog

KFR 6 has been released

14 February 2024

KFR 6 release is out with DFT performance improvements, Multidimensional DFT, easier setup, Windows arm64 support and many new features. See the full list of changes.

KFR 5.2.0 is released

27 November 2023

This release mainly focuses on DFT performance (which has been increased up to 40% on x86 and x86_64) and bug fixes.

KFR 5.1.0 is released

12 October 2023

New window functions, improvements to vec<> class and more.

Simple declarative reflection in C++20

21 December 2022

Almost every real-world application requires a lot of similar operations such as saving its internal state, making API requests, logging events, etc. This leads to writing hundreds of lines of code to convert classes to JSON, serializing to various formats, and so on.

But if we knew the internal structure of classes, then we could write generic functions for all use cases and get the desired features quickly and easily.

KFR 5 has been released

1 December 2022

KFR 5 has been released with new features and performance improvements. Multidimensional arrays, exceptions and better performance.

What's new in KFR 4.0

6 December 2019
IIR filter design New in KFR 4 Butterworth Chebyshev type I and II Bessel Low pass, High pass, Band pass and Band stop Conversion of arbitrary filter from Z,P,K to SOS format (suitable for biquad function and filter) Discrete Cosine Transform support New in KFR 4 Accelerated using KFR FFT C API New in KFR 4 DFT, DCT, convolution, IIR/FIR Filters KFR DFT and related algorithms can now be used with any compiler and any language with ability to call C functions

KFR 3.0 is released

15 March 2019

Here is a brief summary of the major improvements in this release.

What's new in KFR 3.0

15 March 2019

MSVC, GCC and AVX512 as well as DFT with non-power of 2 sizes.

Fast Fourier Transform in C++ using KFR

12 September 2016

In this article I’ll show you how to use Fast Fourier Transform in Digital Signal Processing and how to apply forward and inverse FFT on complex and real data using the KFR framework.