A wonderful triangle in compressed sensing
From MaRDI portal
Publication:6122304
DOI10.1016/j.ins.2022.08.055arXiv2202.09952OpenAlexW4293038572MaRDI QIDQ6122304
No author found.
Publication date: 27 March 2024
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2202.09952
nonconvex optimizationcompressed sensingsparse signal reconstructioniterative soft-thresholding operatorsparsity-promotingthe \(\ell_0\) minimizationthe \(\ell_1/\ell_\infty\) algorithm
Analysis of algorithms (68W40) Convex programming (90C25) Nonlinear programming (90C30) Numerical optimization and variational techniques (65K10) Interior-point methods (90C51)
Cites Work
- Unnamed Item
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- A mathematical introduction to compressive sensing
- Optimal detection of sparse principal components in high dimension
- Stable recovery of sparse signals via \(\ell_p\)-minimization
- Iterative thresholding for sparse approximations
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization
- Sparsest solutions of underdetermined linear systems via \( \ell _q\)-minimization for \(0<q\leqslant 1\)
- Minimization of transformed \(L_1\) penalty: theory, difference of convex function algorithm, and robust application in compressed sensing
- The DC (Difference of convex functions) programming and DCA revisited with DC models of real world nonconvex optimization problems
- Analysis of the ratio of \(\ell_1\) and \(\ell_2\) norms in compressed sensing
- Sparse signal reconstruction via the approximations of \(\ell_0\) quasinorm
- Accelerated iterative hard thresholding algorithm for \(l_0\) regularized regression problem
- Complexity of unconstrained \(L_2 - L_p\) minimization
- Sparsity Constrained Nonlinear Optimization: Optimality Conditions and Algorithms
- Local Linear Convergence of ISTA and FISTA on the LASSO Problem
- Compressed sensing and best 𝑘-term approximation
- Decoding by Linear Programming
- Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
- From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images
- Atomic Decomposition by Basis Pursuit
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- <formula formulatype="inline"><tex Notation="TeX">$L_{1/2}$</tex> </formula> Regularization: Convergence of Iterative Half Thresholding Algorithm
- Sparse Approximate Solutions to Linear Systems
- Reweighted $\ell_1$-Minimization for Sparse Solutions to Underdetermined Linear Systems
- Minimization of $L_1$ Over $L_2$ for Sparse Signal Recovery with Convergence Guarantee
- Difference-of-Convex Algorithms for a Class of Sparse Group $\ell_0$ Regularized Optimization Problems
- Accelerated Schemes for the $L_1/L_2$ Minimization
- A Scale-Invariant Approach for Sparse Signal Recovery
- Minimization of $\ell_{1-2}$ for Compressed Sensing
- Stable signal recovery from incomplete and inaccurate measurements
- On Nonlinear Fractional Programming
- Mathematical Programs with Cardinality Constraints: Reformulation by Complementarity-Type Conditions and a Regularization Method
- Limited-Angle CT Reconstruction via the $L_1/L_2$ Minimization
- Compressed sensing