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A new algorithm implemented as combination of gradient based and single iteration reconstruction algorithms for compressively sensed sparse signals is proposed in the paper. A good feature of the gradient algorithm to perform reconstruction for a wide range of applications is combined with the speed of single iteration algorithm in order to perform faster reconstruction in the cases where single iteration...
Sparse signal reconstruction performed by two different algorithms is considered. First algorithm is the ISTA algorithm for LASSO minimization, while the second one is the gradient-based descent algorithm. Algorithms perform signal reconstruction in a completely different way. The ISTA algorithm reconstructs signals in the sparsity transformation domain. The gradient descent algorithm performs reconstruction...
The reconstruction of video with missing data using a gradient-based compressive sensing algorithm is presented in this paper. The video is assumed to have missing data randomly spread over the frames. Also, it has been assumed that the video frames are sparse in the DCT domain. The value of the gradient is calculated in the sparsity domain and then used to update the pixel values. The efficiency...
Reconstruction of the sparse signals, performed by two algorithms which belongs to the class of convex optimization algorithms, is considered in this paper. Widely used algorithm implemented by the l1-magic code packet is used as the first algorithm. Its realization is based on the primal dual interior point algorithm for convex optimization. The second considered algorithm also belongs to the convex...
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