所属单位：

理学院

发表刊物：

ICIC Express Letters, Part B: Applications

关键字：

中文关键字：鲁棒主成分分析；矩阵补全；低秩矩阵恢复；核范数最小化；增广拉格朗日乘子法，英文关键字：robust principal component analysis; matrix comple

摘要：

This paper studies the problem of incomplete robust principal component analysis (IRPCA) and proposes an iterative algorithm to solve it. The IRPCA problem can be described as a convex program which minimizes a weighted combination of nuclear norm and l1-norm. The inexact augmented Lagrange multiplier method is applied to solve IRPCA and the iterative procedure is developed. Experimental results demonstrate that the proposed method is more effective than other methods in low-rank recovery performance.

备注：

EI期刊检索

合写作者：

雍龙泉

第一作者：

郑秀云,史加荣

论文类型：

期刊论文

卷号：

卷：5

期号：

期：6

页面范围：

页：1531-1538

是否译文：

否

发表时间：

2014-12-01