Calculate Sparse Signal Approximations Using MATLAB Algorithms

Sparsify represents a collection of MATLAB m-files implementing various algorithms to compute sparse signal approximations. The toolbox currently contains two primary algorithm families: greedy methods (categorized as GreedLab) and hard thresholding approaches (organized under HardLab). The implementation includes core functions for orthogonal matching pursuit (OMP), thresholding operations, and regularization techniques, all accessible through a unified interface. This structured framework enables straightforward algorithm comparison and customization through modular function calls. Additionally, Sparsify provides an intuitive user interface that facilitates seamless implementation and experimental testing of these algorithms. Researchers and practitioners can leverage this toolbox to efficiently explore multiple techniques for computing sparse signal approximations tailored to their specific application requirements, with built-in support for signal processing workflows and performance benchmarking.