An improved bound of cumulative coherence for signal recovery

DOI10.1142/S021969131950053XzbMath1434.94025OpenAlexW2953929437MaRDI QIDQ5221431

Peng Li, Pengbo Geng, Chen, Wengu

Publication date: 25 March 2020

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/s021969131950053x

zbMATH Keywords

Dantzig selectorLasso estimatorcumulative coherencequadratically constrained basis pursuit

Mathematics Subject Classification ID

Analysis of algorithms (68W40) Convex programming (90C25) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Numerical methods for inverse problems for boundary value problems involving PDEs (65N21)

Cites Work

• Unnamed Item
• A mathematical introduction to compressive sensing
• On greedy algorithms for dictionaries with bounded cumulative coherence
• Signal recovery under cumulative coherence
• Signal recovery under mutual incoherence property and oracle inequalities
• Stable recovery of analysis based approaches
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
• Decoding by Linear Programming
• Stable recovery of sparse overcomplete representations in the presence of noise
• Sparse representations in unions of bases
• Greed is Good: Algorithmic Results for Sparse Approximation
• Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
• Uncertainty principles and ideal atomic decomposition
• Dictionary Preconditioning for Greedy Algorithms
• Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ ¹ minimization
• Stable signal recovery from incomplete and inaccurate measurements
• Compressed sensing