Orthogonal Matching Pursuit Algorithm for Compressed Sensing Reconstruction

This code implements the compressed sensing reconstruction algorithm in MATLAB, providing a comprehensive understanding of its essential processes and overall algorithmic behavior. The algorithm compresses input signals and reconstructs them using compressed measurements, enabling efficient signal recovery. The implementation includes key components such as signal compression methods, construction of sensing matrices, and optimization algorithms for the reconstruction process. Through detailed examination of this code, users can study specific implementation aspects like sparse representation techniques, measurement matrix design using random projections, and the iterative orthogonal matching pursuit procedure that greedily selects atoms to approximate sparse signals. This deep understanding facilitates mastery of compressed sensing principles and applications, establishing a foundation for further research and practical implementations in signal processing and computational mathematics. The code structure demonstrates core MATLAB functions for matrix operations, optimization routines, and performance evaluation metrics relevant to sparse signal reconstruction.