An Efficient Projected Gradient Method for Convex Constrained Monotone Equations with Applications in Compressive Sensing

• 作者: Yujie Wang
• 来源期刊: 应用数学与应用物理(英文)
• 学科: 数学
• 关键词: Projection Method Monotone Equations Conjugate Gradient Method Compressive Sensing
• 年，卷（期）: 2020,（6）
• 页码范围: 983-998
• 页数: 16页
• 分类号: O17

摘要

In this paper, a modified Polak-Ribière-Polyak conjugate gradient projection method is proposed for solving large scale nonlinear convex constrained monotone equations based on the projection method of Solodov and Svaiter. The obtained method has low-complexity property and converges globally. Furthermore, this method has also been extended to solve the sparse signal reconstruction in compressive sensing. Numerical experiments illustrate the efficiency of the given method and show that such non-monotone method is suitable for some large scale problems.