Restricted q-Isometry Properties Adapted to Frames for Nonconvex l_q-Analysis

2016/02/20 by Junhong Lin, Li Song, Lin, Junhong +1
Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #Image and Signal Denoising Methods #Information Theory (cs.IT) #Mathematical Analysis and Transform Methods #Sparse and Compressive Sensing Techniques

paper · pdf · doi:10.48550/arxiv.1602.06399

openalex publication_date 2016/02/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper discusses reconstruction of signals from few measurements in the situation that signals are sparse or approximately sparse in terms of a general frame via the l_q-analysis optimization with 0

Citations

• Sharp RIP bound for sparse signal and low-rank matrix recovery
• Simultaneous cartoon and texture image inpainting using morphological component analysis (MCA)
• Sparsest solutions of underdetermined linear systems via ℓq-minimization for 0<q⩽1
• Iteratively reweighted least squares minimization for sparse recovery
• Stable signal recovery from incomplete and inaccurate measurements

Related

• New sufficient conditions of signal recovery with tight frames via l₁-analysis
• Compressed Sensing with coherent tight frames via l_q-minimization for 0
• New RIC Bounds via l_q-minimization with 0
• Analysis ℓ₁-recovery with frames and Gaussian measurements
• Signal and Image Reconstruction with Tight Frames via Unconstrained ℓ₁-αℓ₂-Analysis Minimizations