Global ETD Search
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Showing 1 to 9 of 9 for “"Orthogonal matching pursuit"”.
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Accelerated deconvolution of radio interferometric images using orthogonal matching pursuit and graphics hardware
… We present an accelerated implementation of the orthogonal matching pursuit (OMP) algorithm (a compressed sensing method) that makes use of graphics processing unit (GPU) hardware, and show significant accuracy improvements over the standard CLEAN. In particular, we show that OMP correctly …
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Image restoration from noisy and limited measurements with applications in 3D imaging
… problems are considered. First, the Tree-based Orthogonal Matching Pursuit (TOMP) algorithm is proposed to recover sparse signals with tree structure. This is an improvement over the Orthogonal Matching Pursuit method with the incorporation of the sparse-tree prior on the data. A theoretical …
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Acoustic source localization
… -- Disciplined Convex Programming, Orthogonal Matching Pursuit, and Compressive Sensing -- are explored, and their robustness to noise, and sparsity are examined in simulation. Results show that Two-Step Iterative Shrinkage Threshold (TwIST) is the most robust to noisy and non-sparse …
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Radar detection and identification of human signatures using moving platforms
… parameters in a dictionary, and then applies Orthogonal Matching Pursuit (OMP) to determine the optimal linear combination of dictionary entries that comprises the measured radar data. Thus, unlike the ONLP, the EnONLP algorithm also has the capability of detecting the presence of multiple …
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Innovative methods for the reconstruction of new generation satellite remote sensing images
… theory adopting three different strategies (orthogonal matching pursuit, basis pursuit and a genetic algorithm solution) for the reconstruction of cloud-contaminated images; iv) a complete processing chain which exploits a support vector machine (SVM) classification and morphological filters …
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Parallelisation of greedy algorithms for compressive sensing reconstruction
… reconstruction techniques, known as greedy pursuits, reconstruction of large problems can pose a significant burden, consuming a great deal of memory as well as compute time. Parallel computing is the foundation of the field of High Performance Computing (HPC). Modern supercomputers are …
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Sparse Value Function Approximation for Reinforcement Learning
… from sampled data. We consider variants of orthogonal matching pursuit (OMP) applied to RL. The resulting algorithms are analyzed and compared experimentally with existing <italic>L<sub>1</sub></italic> regularized approaches. We demonstrate that perhaps the most natural scenario in which …
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Efficient sequential probability assessment heuristic in decision analysis
Many decision problems involve situations where the possible outcomes are specified but the corresponding probability mass function is only partially known. In such cases, the expected utility of an alternative is not explicitly computable and decisions are made without full information. To address …