Source Code for Compressive Sensing's Classic IHT Algorithm

This implementation features the Iterative Hard Thresholding (IHT) algorithm, a fast and efficient method for reconstructing sparse signals in compressive sensing applications. The algorithm operates through an iterative process where each cycle involves a gradient descent step followed by hard thresholding that retains only the K largest magnitude components (K being the sparsity level). Key functions typically include signal projection, residual calculation, and thresholding operations. The IHT algorithm's significance lies in its ability to recover original signals without requiring prior knowledge of signal structure. The provided source code offers a complete, optimized implementation featuring proper initialization, iteration control, and convergence checks. With clean modular structure and comprehensive comments, the code executes directly without modifications, making it ideal for both compressive sensing research and practical applications requiring sparse signal reconstruction.