Recovery analysis for block ℓp − ℓ1 minimization with prior support information
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Publication:5097858
DOI10.1142/S0219691321500570zbMath1493.90136OpenAlexW3207522052MaRDI QIDQ5097858
Publication date: 1 September 2022
Published in: International Journal of Wavelets, Multiresolution and Information Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1142/s0219691321500570
Convex programming (90C25) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Linear operators and ill-posed problems, regularization (47A52)
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Cites Work
- Compressed sensing with coherent tight frames via \(l_q\)-minimization for \(0 < q \leq 1\)
- New bounds on the restricted isometry constant \(\delta _{2k}\)
- Restricted \(p\)-isometry property and its application for nonconvex compressive sensing
- The restricted isometry property and its implications for compressed sensing
- Sparsest solutions of underdetermined linear systems via \( \ell _q\)-minimization for \(0<q\leqslant 1\)
- Recovery of signals under the condition on RIC and ROC via prior support information
- Recovery analysis for weighted mixed \(\ell_2 / \ell_p\) minimization with \(0 < p \leq 1\)
- Compressed sensing of color images
- A short note on compressed sensing with partially known signal support
- Sharp RIP bound for sparse signal and low-rank matrix recovery
- Restricted $q$-Isometry Properties Adapted to Frames for Nonconvex $l_q$-Analysis
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Decoding by Linear Programming
- A Proof of Conjecture on Restricted Isometry Property Constants $\delta _{tk}\ \left(0<t<\frac {4}{3}\right)$
- Modified-CS: Modifying Compressive Sensing for Problems With Partially Known Support
- Analyzing Weighted $\ell_1$ Minimization for Sparse Recovery With Nonuniform Sparse Models
- Compressed Sensing and Affine Rank Minimization Under Restricted Isometry
- Recovering Compressively Sampled Signals Using Partial Support Information
- Sparse Representation of a Polytope and Recovery of Sparse Signals and Low-Rank Matrices
- A sparse signal reconstruction perspective for source localization with sensor arrays
- Compressed sensing
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