Official Implementation of Compressive Sensing Recovery Algorithm

This documentation provides the official MATLAB implementation of Compressive Sensing recovery algorithms, designed to facilitate better understanding and application of these methods. The package includes complete source code featuring key algorithms such as basis pursuit, matching pursuit, and optimization-based reconstruction techniques. Alongside the implementation, we provide comprehensive PDF documentation detailing the mathematical foundations, practical applications, and advantages of compressive sensing methodology. The documentation explains core concepts including sparse signal representation, measurement matrices, and recovery conditions. Additionally, we include practical examples demonstrating proper usage scenarios and performance evaluation metrics, showing signal reconstruction from limited measurements using ℓ1-minimization and greedy approaches. These resources collectively support deeper comprehension of algorithm implementation and optimization strategies for compressive sensing applications.