Spike detection from inaccurate samplings
From MaRDI portal
Publication:2512831
DOI10.1016/j.acha.2014.03.004zbMath1308.94046arXiv1301.5873OpenAlexW2057603175MaRDI QIDQ2512831
Yohann de Castro, Jean-Marc Azaïs, Fabrice Gamboa
Publication date: 30 January 2015
Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1301.5873
Semidefinite programming (90C22) Detection theory in information and communication theory (94A13) Sampling theory in information and communication theory (94A20)
Related Items (44)
Supermix: sparse regularization for mixtures ⋮ On the uniqueness of solutions for the basis pursuit in the continuum ⋮ Robust recovery of stream of pulses using convex optimization ⋮ Degrees of freedom for off-the-grid sparse estimation ⋮ Point source super-resolution via non-convex \(L_1\) based methods ⋮ Generalized notions of sparsity and restricted isometry property. II: Applications ⋮ Super-resolution wavelets for recovery of arbitrarily close point-masses with arbitrarily small coefficients ⋮ Sparse non-negative super-resolution -- simplified and stabilised ⋮ Stable super-resolution limit and smallest singular value of restricted Fourier matrices ⋮ When does OMP achieve exact recovery with continuous dictionaries? ⋮ Approximate super-resolution of positive measures in all dimensions ⋮ Exact support recovery for sparse spikes deconvolution ⋮ Sampling the Fourier Transform Along Radial Lines ⋮ A diffusion + wavelet-window method for recovery of super-resolution point-masses with application to single-molecule microscopy and beyond ⋮ Dynamical programming for off-the-grid dynamic inverse problems ⋮ Dynamic Spike Superresolution and Applications to Ultrafast Ultrasound Imaging ⋮ The geometry of off-the-grid compressed sensing ⋮ IFF: A Superresolution Algorithm for Multiple Measurements ⋮ Dynamic super-resolution in particle tracking problems ⋮ Adapting to unknown noise level in sparse deconvolution ⋮ Super-resolution of point sources via convex programming ⋮ Atomic norm minimization for decomposition into complex exponentials and optimal transport in Fourier domain ⋮ Sparse spikes super-resolution on thin grids II: the continuous basis pursuit ⋮ TV-based reconstruction of periodic functions ⋮ A fast homotopy algorithm for gridless sparse recovery ⋮ MultiDimensional Sparse Super-Resolution ⋮ Support recovery for sparse super-resolution of positive measures ⋮ Sparse polynomial interpolation: sparse recovery, super-resolution, or Prony? ⋮ On algebraic properties of low rank approximations of Prony systems ⋮ Super-resolution by means of Beurling minimal extrapolation ⋮ Testing Gaussian process with applications to super-resolution ⋮ Stability and super-resolution of generalized spike recovery ⋮ Accuracy of reconstruction of spike-trains with two near-colliding nodes ⋮ Super-Resolution of Positive Sources: The Discrete Setup ⋮ Multi-kernel unmixing and super-resolution using the modified matrix pencil method ⋮ The sliding Frank–Wolfe algorithm and its application to super-resolution microscopy ⋮ Approximate support recovery of atomic line spectral estimation: a tale of resolution and precision ⋮ Super-resolution of positive sources on an arbitrarily fine grid ⋮ Sparsest piecewise-linear regression of one-dimensional data ⋮ Inverse point source location with the Helmholtz equation on a bounded domain ⋮ Linear convergence of accelerated conditional gradient algorithms in spaces of measures ⋮ TV-based spline reconstruction with Fourier measurements: uniqueness and convergence of grid-based methods ⋮ Quantization for spectral super-resolution ⋮ Non-uniform spline recovery from small degree polynomial approximation
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Exact reconstruction using Beurling minimal extrapolation
- Super-resolution from noisy data
- Exact support recovery for sparse spikes deconvolution
- A general expression for the distribution of the maximum of a Gaussian field and the approximation of the tail
- Variational methods in imaging
- Superresolution via Sparsity Constraints
- Convergence rates of convex variational regularization
- Sets of Superresolution and the Maximum Entropy Method on the Mean
- Superresolution Rates in Prokhorov Metric
- A convergence rates result for Tikhonov regularization in Banach spaces with non-smooth operators
- Error estimates for non-quadratic regularization and the relation to enhancement
This page was built for publication: Spike detection from inaccurate samplings
