Double Least Squares Pursuit for Sparse Decomposition
Wanyi Li; Peng Wang; Hong Qiao
2012
发表期刊Intelligent Information Processing VI
期号no页码:357-363
摘要
; Sparse decomposition has been widely used in numerous applications, such as image processing, pattern recognition, remote sens-ing and computational biology. Despite plenty of theoretical develop-ments have been proposed, developing, implementing and analyzing novel fast sparse approximation algorithm is still an open problem. In this paper, a new pursuit algorithm Double Least Squares Pursuit (DLSP) is proposed for sparse decomposition. In this algorithm, the support of the solution is obtained by sorting the coefficients which are calculated by the first Least-Squares, and then the non-zero values over this sup-port are detected by the second Least-Squares. The results of numerical experiment demonstrate the effectiveness of the proposed method, which is with less time complexity, more simple form, and gives close or even better performance compared to the classical Orthogonal Matching Pursuit (OMP) method.
关键词Sparse Decomposition Sparse Representation Sparse Approximation Algorithm Double Least-squares Pursuit.
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/12602
专题复杂系统管理与控制国家重点实验室_机器人理论与应用
通讯作者Wanyi Li
作者单位Institute of Automation, Chinese Academy of Sciences
推荐引用方式
GB/T 7714
Wanyi Li,Peng Wang,Hong Qiao. Double Least Squares Pursuit for Sparse Decomposition[J]. Intelligent Information Processing VI,2012(no):357-363.
APA Wanyi Li,Peng Wang,&Hong Qiao.(2012).Double Least Squares Pursuit for Sparse Decomposition.Intelligent Information Processing VI(no),357-363.
MLA Wanyi Li,et al."Double Least Squares Pursuit for Sparse Decomposition".Intelligent Information Processing VI .no(2012):357-363.
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