OMP Algorithm for Compressed Sensing: Signal Recovery via Orthogonal Matching Pursuit

Implementation of 1-D signal compressed sensing using Orthogonal Matching Pursuit (OMP) algorithm, where the number of measurements M>=K*log(N/K) with K representing sparsity and N being signal length, enabling near-perfect reconstruction. The algorithm implementation includes greedy iterative selection of atoms from the sensing matrix, residual updating, and least-squares solution for coefficient estimation. Developed by Wei Sha from the University of Hong Kong's Department of Electrical Engineering (Email: wsha@eee.hku.hk). Reference: Joel A. Tropp and Anna C. Gilbert's seminal paper on signal recovery from random measurements.