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Ingeniería e Investigación
versão impressa ISSN 0120-5609
Resumo
LOBATO POLO, Adriana Patricia; RUIZ CORAL, Rafael Humberto; QUIROGA SEPULVEDA, Julián Armando e RECIO VELEZ, Adolfo León. Sparse signal recovery using orthogonal matching pursuit (OMP). Ing. Investig. [online]. 2009, vol.29, n.2, pp.112-118. ISSN 0120-5609.
Compressive sensing is an emergent field of signal processing which states that a small number of non-adaptive linear projections on a compressible signal contain enough information to reconstruct and process it. This paper presents the results of evaluating 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 subsequent analysis of their suitability for specific applications.
Palavras-chave : compressed sensing; orthogonal matching pursuit; measurement matrix.