Sparse spikes super-resolution on thin grids II: the continuous basis pursuit
DOI10.1088/1361-6420/aa7fcezbMath1392.35332OpenAlexW2608482034MaRDI QIDQ5368862
Publication date: 11 October 2017
Published in: Inverse Problems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1088/1361-6420/aa7fce
convex optimizationsparsityLassosuper-resolutioncontinuous basis pursuit (C-BP)first order approximation of the kernelspikes recognition
Convex programming (90C25) Optimality conditions and duality in mathematical programming (90C46) Approximation methods and heuristics in mathematical programming (90C59) Inverse problems for PDEs (35R30) Numerical methods for inverse problems for boundary value problems involving PDEs (65N21) Inverse problems in optimal control (49N45)
Related Items (12)
Uses Software
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
- Particular formulae for the Moore--Penrose inverse of a columnwise partitioned matrix
- Exact support recovery for sparse spikes deconvolution
- An introduction to \(\Gamma\)-convergence
- Spike detection from inaccurate samplings
- On Sparse Representations in Arbitrary Redundant Bases
- Atomic Decomposition by Basis Pursuit
- Variational Analysis
- Recovery of Sparse Translation-Invariant Signals With Continuous Basis Pursuit
- Inverse problems in spaces of measures
- Superresolution without separation
- Sparse regularization on thin grids I: the Lasso
- Towards a Mathematical Theory of Super‐resolution
- Convex analysis and monotone operator theory in Hilbert spaces
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