文档介绍：压缩感知中迂回式匹配追踪算法基金项目:国家自然科学基金项目(61372049, 61379115, 61100215, 61311140261, 61070180);湖南省自然科学基金项目(13JJ8006, 12JJ9021);湖南省科技厅科技计划项目(2011GK3200);湖南省重点学科建设项目(无编号)
裴廷睿1,2 杨术1,2 李哲涛1,2,3* 谢井雄1,2
1(湘潭大学信息工程学院湖南湘潭 411105)
2(湘潭大学智能计算与信息处理教育部重点实验室湖南湘潭 411105)
3(国防科学技术大学计算机学院长沙 410073)
(chu5044130@)
Detouring Matching Pursuit Algorithm pressed Sensing
Pei Tingrui1,2, Yang Shu1,2 , Li Zhetao1,2,3* and Xie Jingxiong1,2
1(The College of Information Engineering, Xiangtan University, Xiangtan, Hunan 411105)
2(Key Laboratory of puting & Information Processing, Ministry of Education, Xiangtan University, Xiangtan, Hunan 411105)
3(School puter, National University of Defense Technology, Changsha 410073)
Abstract Detouring matching pursuit (DMP) is a greedy algorithm of reconstructive sparse signals with plexity, high accuracy and low column-correlation demand for sensing matrix. The increasing and deceasing formulas of the submatrix’s inner-product and the coefficient matrix in the DMP are put forward and proved. By using the inverse of submatrix’s inner-product and the coefficient matrix, DMP could reduce the amount of calculation of residual error’s variable quantity and obtain plexity in the end. In addition, by using the method of decreasing firstly, and then increasing the element of the assumed support set one by one optimally, DMP could improve the reconstructive accuracy and broa