• Medientyp: E-Artikel
  • Titel: Block sparse vector recovery for compressive sensing via ℓ1−αℓq$\ell _1-\alpha \ell _q$‐minimization Model
  • Beteiligte: Shi, Hongyan; Xie, Shaohua; Wang, Jiangtao
  • Erschienen: Institution of Engineering and Technology (IET), 2024
  • Erschienen in: Electronics Letters, 60 (2024) 2
  • Sprache: Englisch
  • DOI: 10.1049/ell2.13081
  • ISSN: 1350-911X; 0013-5194
  • Schlagwörter: Electrical and Electronic Engineering
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: AbstractThis paper solves the problem of block sparse vector recovery using the block ‐minimization model. Based on the block restricted isometry property (B‐RIP) condition, exact block sparse vector recovery result is obtained. The theoretical bound for the block ‐minimization model are also obtained when measurements are depraved by the noises.
  • Zugangsstatus: Freier Zugang