The dspp library is designed for high performance signal processing. It requires a C++11 or newer compiler and makes good use of modern techniques and the Standard Template Library.

A good math library should have formulas describing how the functions work. So you'll find formulas, examples, and descriptions for everything. Math is displayed using MathJax. You can right-click or ctrl-click on any formula to bring up a menu. Give it a try:

\[\begin{gather} \nabla \cdot \mathbf{D} = \rho_\text{f} \\ \nabla \cdot \mathbf{B} = 0 \\ \nabla \times \mathbf{E} = -\frac{\partial \mathbf{B}} {\partial t} \\ \nabla \times \mathbf{H} = \mathbf{J}_\text{f} + \frac{\partial \mathbf{D}} {\partial t} \end{gather}\]

A testing framework is part of the dspp library and all commits are verified with a continuous integration server. You can also use this framework for testing your own applications, if you so desire. The testing framework includes a benchmarking tool. This makes it difficult to accidentally regress performance and easy to test different implementations. You can be confident that performance is suitable for real-time applications like Software Defined Radio.

Installation

Download or clone from GitHub. https://github.com/AE9RB/dspp
Add the include directory to your compiler include path.
#include <dspp.hpp>

The dspp library is a collection of headers like the Standard Template Library. There's nothing to compile except your own application. There are no dependencies to install. The only thing you need to bring to the party is a C++11 compiler.

Contribute

View the README on GitHub to learn more. Submit a pull request when you have something to contribute.