#Residual Minimization Pursuit (RMP)

A new sparse signal recovery algorithm, dubbed as Residual Minimization Pursuit (RMP), was proposed for compressive sensing signal reconstruction. This algorithm iteratively detects the support set of the true signal by selecting the element with the largest magnitude of the orthogonal projection of residual signal onto the measurements matrix, then it updates the unknown signal using least-squares solution on detecting support set. In addition, two support detection strategies were devised by spotting several elements in each iteration. The experimental studies are presented to demonstrate that the RMP offers an attractive alternative to OMP for sparse signal recovery.