Open AccessBlock normalised iterative hard thresholding algorithm for compressed sensing
Author(s) -
Zhang Xiaobo,
Xu Wenbo,
Lin Jiaru,
Dang Yifei
Publication year - 2019
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2019.1795
Subject(s) - block (permutation group theory) , algorithm , thresholding , restricted isometry property , convergence (economics) , compressed sensing , property (philosophy) , computer science , mathematics , block size , iterative method , artificial intelligence , combinatorics , image (mathematics) , philosophy , computer security , epistemology , key (lock) , economics , economic growth
In this letter, the authors propose block normalised iterative hard thresholding (BNIHT) algorithm for the recovery of block sparse signal, in which the non‐zero elements are presented in clusters. Based on block restricted isometry property, the sufficient conditions to guarantee the convergence of BNIHT are derived. In addition, the number of required iterations is obtained. The simulation experiment shows that BNIHT algorithm is superior to the block IHT (BIHT) algorithm when the step size satisfies μ < 1 .