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Modified Iterative Method for Recovery of Sparse Multiple Measurement Problems



Author(s)

Sina Mortazavi and Reza Hosseini

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DOI:10.17265/2328-2223/2018.02.009

We consider the problem of constructing one sparse signal from a few measurements. This problem has been extensively addressed in the literature, providing many sub-optimal methods that assure convergence to a locally optimal solution under specific conditions. There are a few measurements associated with every signal, where the size of each measurement vector is less than the sparse signal’s size. All of the sparse signals have the same unknown support. We generalize an existing algorithm for the recovery of one sparse signal from a single measurement to this problem and analyze its performances through simulations. We also compare the construction performance with other existing algorithms. Finally, the proposed method also shows advantages over the OMP (Orthogonal Matching Pursuit) algorithm in terms of the computational complexity.

Sparse signal recovery, iterative methods, multiple measurements.