Orthogonal Matching Pursuit with Shannon Sampling
Recent work of orthogonal matching pursuit with partially known support shows that this algorithm has better performance than traditional orthogonal matching pursuit. However, there is lack of theoretical guarantee for the algorithm. In this paper, we propose a new algorithm which combines orthogonal matching pursuit with Shannon sampling and obtain the theoretical guarantee for our method. In our proposed method we measure partially known support part of a sparse signal with Shannon sampling and measure the rest part with compressive sensing. Then we can reconstruct the rest part directly with orthogonal matching pursuit and get the theoretical guarantee. Comparisons with previous related works are shown.
compressrve sensing orthogonal matching pursuit Shannon sampling theoretical guarantee sparse
Zhulou Cao Enqing Dong
School of Mathematics and Statistics Shandong University at Weihai Weihai, China School of Mechatronics and Information Engineering Shandong University at Weihai Weihai, China
国际会议
重庆
英文
146-149
2011-01-21（万方平台首次上网日期，不代表论文的发表时间）