%0 Journal Article
%T Sparse signal recovery using orthogonal matching pursuit (OMP)
%A Adolfo Le¨®n Recio V¨¦lez
%A Adriana Patricia Lobato Polo
%A Juli¨¢n Armando Quir¨®ga Sep¨²lveda
%A Rafael Humberto Ruiz Coral
%J -
%D 2009
%X Compressive sensing is an emergent field of signal processing which states that a small number of non-adaptive linear project- tions on a compressible signal contain enough information to reconstruct and process it. This paper presents the results of e- valuating five measurement matrices for applying them to compressive sensing in a system using orthogonal matching pursuit (OMP) to reconstruct the original signal. The measurement matrices were those implicated in compressive sensing as well as in reconstructing the signal. The Hadamard-random matrix stood out within this group of matrices because the lowest percentage of error in signal recovery was obtained with it. This paper also presents a methodology for evaluating these matrices, allowing sub- sequent analysis of their suitability for specific applications
%K compressed sensing
%K orthogonal matching pursuit
%K measurement matrix
%U https://revistas.unal.edu.co/index.php/ingeinv/article/view/15171