A modified sequential quadratic programming method for sparse signal recovery problems

被引：3
|
作者：
Alamdari, Mohammad Saeid [1 ]
Fatemi, Masoud [1 ]
Ghaffari, Aboozar [2 ]
机构：
[1] KN Toosi Univ Technol, Dept Math, Tehran, Iran
[2] Iran Univ Sci & Technol, Dept Elect Engn, Tehran, Iran
来源：
SIGNAL PROCESSING | 2023年 / 207卷
关键词：
Sparse signal recovery; Sequential programming method; SL0; approximation; Non-convex optimization; ALGORITHM; CONVERGENCE; SYSTEM;
D O I：
10.1016/j.sigpro.2023.108955
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We propose a modified sequential quadratic programming method for solving the sparse signal recovery problem. We start by going through the well-known smoothed-l(0) technique and provide a smooth ap-proximation of the objective function. Then, a variant of the sequential quadratic programming method equipped with a new approach for solving subproblems is proposed. We investigate the global con-vergence of the method in detail. In comparison to several well-known algorithms, simulation results demonstrate the promising performance of the proposed method.(c) 2023 Elsevier B.V. All rights reserved.
引用
收藏
页数：10
相关论文
共 50 条
12345