A modified primal-dual method with applications to some sparse recovery problems

作者：

Highlights：

• A convex composite optimization which includes sparse recovery problems is studied.

• A modified Chambolle–Pock primal-dual method (MCPPDM) is proposed.

• MCPPDM only needs little additional computation cost.

• MCPPDM is proved to be globally convergent.

• Numerical experiments show the efficiency of the proposed method.

摘要

•A convex composite optimization which includes sparse recovery problems is studied.•A modified Chambolle–Pock primal-dual method (MCPPDM) is proposed.•MCPPDM only needs little additional computation cost.•MCPPDM is proved to be globally convergent.•Numerical experiments show the efficiency of the proposed method.

论文关键词：Primal-dual method,Proximity operator,Sparse recovery problems

论文评审过程：Received 2 November 2017, Revised 28 January 2018, Accepted 21 March 2018, Available online 10 April 2018, Version of Record 10 April 2018.

论文官网地址：https://doi.org/10.1016/j.amc.2018.03.089