Double Least Squares Pursuit for Sparse Decomposition

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	Double Least Squares Pursuit for Sparse Decomposition
	Wanyi Li; Peng Wang; Hong Qiao
发表期刊	Intelligent Information Processing VI
	2012
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	多模态人工智能系统全国重点实验室_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.