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Showing 1 to 8 of 8 for “"L1-minimization"”.
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Seismic ground-roll separation using sparsity promoting L1 minimization
The removal of coherent noise generated by surface waves in land based seismic is a prerequisite to imaging the subsurface. These surface waves, termed as ground roll, overlay important reflector information in both the t-x and f-k domains. Standard techniques of ground roll removal commonly alter …
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Fast and robust face recognition via parallelized L1 minimization
… extract low-dimensional features. Several custom L1 solvers are presented that achieve faster convergence on face data than general solvers. Optimized implementations for modern parallel computing architectures are investigated in order to build a system capable of performing highly accurate and …
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On the Local Correctness of L1-minimization for Dictionary Learning Algorithm
Item withdrawn by Rebecca Bryant (rabryant@illinois.edu) on 2011-12-01T20:45:07Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 GENG_QUAN.pdf: 460059 bytes, checksum: 9fe702d7efe57d2efd8da6d4af67f05b (MD5)
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Selection of Step Size for Total Variation Minimization in CT
… image reconstruction by total variation minimization is a newly developed area in computed tomography (CT). In compressed sensing literature, it hasbeen shown that signals with sparse representations in an orthonormal basis may be reconstructed via l1-minimization. Furthermore, if an …
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Mathematical analysis of a dynamical system for sparse recovery
… Second, these results are specialized to the L1-minimization problem, which is the most famous approach to solving the sparse recovery problem. The analysis relies on standard techniques in CS and proves that the network takes an efficient path toward the solution for parameters that match …
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High-resolution source imaging with bio-inspired sensing systems
… the output images. First, we provide a new l1-minimization algorithm using a backward basis elimination technique. The algorithm outperforms the well-known l1magic package for small-scale problems. This algorithm can be used in the sparse beamforming application. Second, we introduce the …
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Bridging Mri Reconstruction Across Eras: From Novel Optimization Of Traditional Methods To Efficient Deep Learning Strategies
… for non-Cartesian imaging. We first revisited l1-wavelet CS reconstruction for accelerated MRI by using modern data science tools similar to those used in DL for optimized performance. We showed that our proposed optimization approach improved traditional CS, and further performance boost was …
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Use of the Traffic Speed Deflectometer for Concrete and Composite Pavement Structural Health Assessment: A Big-Data-Based Approach Towards Concrete and Composite Pavement Management and Rehabilitation
… scheme [Basis Pursuit coupled with Reweighted L1 Minimization] to simultaneously remove the white noise from the TSD deflection measurements and extract the deflection response generated as the TSD travels over the pavement's transverse joints. The examples presented demonstrate that this …