A new smoothing modified three-term conjugate gradient method for l1-norm minimization problem

被引:0
作者
Du, Shouqiang [1 ]
Chen, Miao [1 ]
机构
[1] Qingdao Univ, Sch Math & Stochast, Qingdao, Peoples R China
基金
中国国家自然科学基金;
关键词
Nonsmooth optimization problem; Smoothing modified three-term conjugate gradient method; Global convergence; THRESHOLDING ALGORITHM; NONSMOOTH; L(1)-MINIMIZATION; CONVERGENCE; PROJECTION; EQUATIONS;
D O I
10.1186/s13660-018-1696-9
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We consider a kind of nonsmooth optimization problems with l(1)-norm minimization, which has many applications in compressed sensing, signal reconstruction, and the related engineering problems. Using smoothing approximate techniques, this kind of nonsmooth optimization problem can be transformed into a general unconstrained optimization problem, which can be solved by the proposed smoothing modified three-term conjugate gradient method. The smoothing modified three-term conjugate gradient method is based on Polak-Ribiere-Polyak conjugate gradient method. For the Polak-Ribiere-Polyak conjugate gradient method has good numerical properties, the proposed method possesses the sufficient descent property without any line searches, and it is also proved to be globally convergent. Finally, the numerical experiments show the efficiency of the proposed method.
引用
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页数:14
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