Analysis non-sparse recovery for non-convex relaxed $\ell_q$ minimization Published: 2021/11/29 Jianwen HuangFeng ZhangXinling LiuJianjun WangCategories Data-Mining, Nonsmooth Optimization, Unconstrained Optimization Tags $\ell_q$ robust $D$-Null Space Property, compressed sensing, Non-convex relaxed $\ell_q$ minimization method, Restricted isometry property adapted $D$, sparse recovery Short URL: https://optimization-online.org/?p=18347 This paper studies construction of signals, which are sparse or nearly sparse with respect to a tight frame $D$ from underdetermined linear systems. In the paper, we propose a non-convex relaxed $\ell_q(0 ArticleDownload View PDF