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Tensor compressive sensing (TCS) is a multidimensional framework of compressive sensing (CS), and it is advantageous in terms of reducing the amount of storage, easing hardware implementations, and preserving multidimensional structures of signals in comparison to a conventional CS system. In a TCS system, instead of using a random sensing matrix and a predefined dictionary, the average-case performance...
Sparse signals can be sensed with a reduced number of random projections and then reconstructed if compressive sensing (CS) is employed. Traditionally, the projection matrix has been chosen as a random Gaussian matrix, but improved reconstruction performance can be obtained by optimizing the projection matrix. In this paper, we are interested in projection matrix designs for sensing sparse signals...
Penumbral imaging is a power imaging technique for radiations with long mean-free path. Since the reconstruction is based on deconvolution, the technique is sensitive to noise contained in penumbral images. The reconstruction of penumbral images can be viewed as an optimization problem by optimizing its cost function. Though conventional local optimization techniques, such as the gradient decent method,...
In this paper, we propose an evolutionary perturbation algorithm of Simulated Annealing in optimization of kinoform. At the optimization of the kinoform, the perturbation of the Simulated Annealing is determined by result of the previous perturbation. The evolutionary perturbation can improve the convergence of cost function of the optimization. Computer simulation demonstrated that the proposed method...
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