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Sparse signals can be sensed with a reduced number of projections and then reconstructed if compressive sensing is employed. Traditionally, the projection matrix is chosen as a random matrix, but a projection sensing matrix that is optimally designed for a certain class of signals can further improve the reconstruction accuracy. This paper considers the problem of designing the projection matrix Φ...
In this paper, a new method is proposed to optimize the projection matrix, which, unlike the existing approaches, attempts to choose the projection matrix such that the sensing matrix is as close to a tight frame/equiangular tight frame as possible. In the proposed method, there are two important procedures that are used to adjust the Gram matrix of the sensing matrix. The simulation results are presented...
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