Compressed sensing with structured sparsity and structured acquisition
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Publication:1713639
DOI10.1016/j.acha.2017.05.005zbMath1454.94010arXiv1505.01619OpenAlexW1800346269MaRDI QIDQ1713639
Jérémie Bigot, Pierre Weiss, Claire Boyer
Publication date: 25 January 2019
Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1505.01619
Estimation in multivariate analysis (62H12) Applications of mathematical programming (90C90) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
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Cites Work
- Unnamed Item
- A mathematical introduction to compressive sensing
- Generalized sampling and infinite-dimensional compressed sensing
- User-friendly tail bounds for sums of random matrices
- On minimal trajectories for mobile sampling of bandlimited fields
- Beyond sparsity: recovering structured representations by \({\ell}^1\) minimization and greedy algorithms
- An Algorithm for Variable Density Sampling with Block-Constrained Acquisition
- Optimization with Sparsity-Inducing Penalties
- BREAKING THE COHERENCE BARRIER: A NEW THEORY FOR COMPRESSED SENSING
- Sampling High-Dimensional Bandlimited Fields on Low-Dimensional Manifolds
- The Quest for Optimal Sampling: Computationally Efficient, Structure-Exploiting Measurements for Compressed Sensing
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Just relax: convex programming methods for identifying sparse signals in noise
- Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
- Why do commercial CT scanners still employ traditional, filtered back-projection for image reconstruction?
- Structured Compressed Sensing: From Theory to Applications
- Performance Bounds for Grouped Incoherent Measurements in Compressive Sensing
- Stable and Robust Sampling Strategies for Compressive Imaging
- Robust Recovery of Signals From a Structured Union of Subspaces
- Variable Density Sampling with Continuous Trajectories
- On the Absence of Uniform Recovery in Many Real-World Applications of Compressed Sensing and the Restricted Isometry Property and Nullspace Property in Levels
- On the Generation of Sampling Schemes for Magnetic Resonance Imaging
- A Probabilistic and RIPless Theory of Compressed Sensing
- Recovering Low-Rank Matrices From Few Coefficients in Any Basis
- Model-Based Compressive Sensing
- Exact Recovery Conditions for Sparse Representations With Partial Support Information
- Stable signal recovery from incomplete and inaccurate measurements
- Compressed sensing
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