Date of Publication :7th August 2016
Abstract: Compressive Sensing (CS) signal reconstruction can be implemented using convex relaxation, non-convex, or local optimization algorithms. Though the re- construction using convex optimization, such as the Iterative Hard Thresholding algorithm is more accurate than matching pursuit algorithms, most researchers focus on matching pursuit algorithms because they are less computationally complex. Orthogonal Matching Pursuit (OMP) is a greedy algorithm, which solves the problem by choosing the most significant variable to reduce the least square error. Simultaneous OMP is an extension of OMP algorithm which contain multiple measurement vector (MMV). In this paper, we present an architecture by using VHDL for the reconstruction of compressively sensed signal using the orthogonal matching pursuit (OMP) and simultaneous OMP.
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