Sparse Recovery With Block Multiple Measurement Vectors Algorithm
This paper investigates the performance of the block multiple measurement vectors (BMMV) algorithm in reconstructing block joint sparse matrices. We prove that if 41) obeys block restricted isometry property with 8 K+1 <; Nf +1 , then BMMV perfectly reconstructs any block K -joint sparse matr...
Main Authors: | Yanli Shi, Libo Wang, Rong Luo |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8614434/ |
Similar Items
-
On Recovery of Block Sparse Signals via Block Compressive Sampling Matching Pursuit
by: Xiaobo Zhang, et al.
Published: (2019-01-01) -
Non-convex block-sparse compressed sensing with coherent tight frames
by: Xiaohu Luo, et al.
Published: (2020-01-01) -
A new bound on the block restricted isometry constant in compressed sensing
by: Yi Gao, et al.
Published: (2017-08-01) -
Grassmannian Fusion Frames for Block Sparse Recovery and Its Application to Burst Error Correction
by: Mukund Sriram, N
Published: (2018) -
New Bounds Based on RIP for the Sparse Matrix Recovery via the Weighted <inline-formula> <tex-math notation="LaTeX">$\ell_{2,1}$ </tex-math></inline-formula> Minimization
by: Huanmin Ge, et al.
Published: (2019-01-01)