July 24

This subdirectory contains the following Matlab source codes:

run_code_LL.m
run_code_LS_lou.m
run_code_RCS.m           Run_code. Can be run directly after creating a folder named "Results"

MBA_l1vl2_LL.m           Implementation of MBA_l1/l2 for minimizing L1/L2 subject to Lorentzian norm
MBA_l1vl2_LS.m           Implementation of MBA_l1/l2 for minimizing L1/L2 subject to Least squares loss function
MBA_l1vl2_RCS.m          Implementation of MBA_l1/l2 for minimizing L1/L2 for robust compressed sensing

SCP_ls_LL2.m             Implementation of SCP_ls for minimizing L1 subject to Lorentzian norm

CaseSg.m
SubP_alpha.m             Subroutines for MBA codes and the SCP code

Implementation and numerical experience with the above codes are described in the paper: 
    Liaoyuan Zeng, Peiran Yu and Ting Kei Pong
    "Analysis and algorithms for some compressed sensing models based on L1/L2 minimization",
    Submitted.
This code was last updated on July 23, 2020.

Questions/comments/suggestions about the codes are welcome.  

Ting Kei Pong tk.pong@polyu.edu.hk