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A new sufficient condition for sparse vector recovery via ℓ1 − ℓ2 local minimization - MaRDI portal

A new sufficient condition for sparse vector recovery via ℓ1 − ℓ2 local minimization (Q5016825)

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scientific article; zbMATH DE number 7442755

Language	Label	Description	Also known as
English	A new sufficient condition for sparse vector recovery via ℓ1 − ℓ2 local minimization	scientific article; zbMATH DE number 7442755

Statements

scholarly article

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A new sufficient condition for sparse vector recovery via ℓ1 − ℓ2 local minimization (English)

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Analysis and Applications

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publication date

13 December 2021

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zbMATH Keywords

compressive sensing

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\(\ell_1\)-\( \ell_2\) minimization

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sparse vector

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vector recovery

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MaRDI profile type

MaRDI publication profile

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Sharp RIP bound for sparse signal and low-rank matrix recovery

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Sparse Representation of a Polytope and Recovery of Sparse Signals and Low-Rank Matrices

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The restricted isometry property and its implications for compressed sensing

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Decoding by Linear Programming

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Iteratively reweighted least squares minimization for sparse recovery

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Restricted Isometry Constants Where $\ell ^{p}$ Sparse Recovery Can Fail for $0≪ p \leq 1$

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A Method for Finding Structured Sparse Solutions to Nonnegative Least Squares Problems with Applications

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A note on guaranteed sparse recovery via \(\ell_1\)-minimization

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Sparsest solutions of underdetermined linear systems via \( \ell _q\)-minimization for \(0<q\leqslant 1\)

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A mathematical introduction to compressive sensing

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DC programming and DCA: thirty years of developments

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DC approximation approaches for sparse optimization

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Analysis of Sparse Representation and Blind Source Separation

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Computational Aspects of Constrained L 1-L 2 Minimization for Compressive Sensing

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Computing sparse representation in a highly coherent dictionary based on difference of \(L_1\) and \(L_2\)

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New bounds on the restricted isometry constant \(\delta _{2k}\)

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Sparse recovery by non-convex optimization - instance optimality

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Convex analysis approach to d. c. programming: Theory, algorithms and applications

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Stable recovery of sparse signals via \(\ell_p\)-minimization

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The Improved Bounds of Restricted Isometry Constant for Recovery via <formula formulatype="inline"><tex Notation="TeX">$\ell_{p}$</tex> </formula>-Minimization

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Minimization of $\ell_{1-2}$ for Compressed Sensing

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<formula formulatype="inline"><tex Notation="TeX">$L_{1/2}$</tex> </formula> Regularization: Convergence of Iterative Half Thresholding Algorithm

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Optimal RIP bounds for sparse signals recovery via \(\ell_p\) minimization

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full work available at URL

https://doi.org/10.1142/s0219530521500068

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Identifiers

zbMATH Open document ID

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10.1142/S0219530521500068

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:5016825

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