Dimension reduction, exact recovery, and error estimates for sparse reconstruction in phase space

DOI10.1016/j.acha.2024.101631arXiv2112.09743OpenAlexW4390754772MaRDI QIDQ6122631

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Publication date: 1 March 2024

Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2112.09743

zbMATH Keywords

Radon transformdimension reductionconvex programmingRadon measuresoptimal transportsuperresolution

Mathematics Subject Classification ID

Convex programming (90C25) Radon transform (44A12) Spaces of measures, convergence of measures (28A33) Numerical solution to inverse problems in abstract spaces (65J22) Optimal transportation (49Q22)

Cites Work

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• Exact reconstruction using Beurling minimal extrapolation
• Super-resolution from noisy data
• Support recovery for sparse super-resolution of positive measures
• Support theorems for the Radon transform and Cramér-Wold theorems
• Reconstructing plane sets from projections
• The calibration method for the Mumford-Shah functional and free-discontinuity problems
• CVXPY: A Python-Embedded Modeling Language for Convex Optimization
• How Many Points Can Be Reconstructed from k Projections?
• Convergence rates of convex variational regularization
• Dynamic Spike Superresolution and Applications to Ultrafast Ultrasound Imaging
• The smallest sets of points not determined by their X-rays
• Towards a Mathematical Theory of Super‐resolution
• The Alternating Descent Conditional Gradient Method for Sparse Inverse Problems
• On projections of probability distributions
• A generalized conditional gradient method for dynamic inverse problems with optimal transport regularization

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