全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于优化内积模型的压缩感知快速重构算法

DOI: 10.13190/jbupt.201301.19.liuy, PP. 19-22

Keywords: 优化内积,压缩感知,重构算法

Full-Text   Cite this paper   Add to My Lib

Abstract:

针对压缩感知理论中现有重构算法耗时过长的问题,提出一种基于优化内积模型的快速重构算法,且理论推导了迭代停止条件.该算法在重构的每次迭代过程中,仅在第1次迭代时采用传感矩阵与余量的矩阵求内积运算,在后续的迭代中则通过向量运算代替矩阵求内积的运算,迭代停止时只需进行一次最小二乘法即可获得重构信号.仿真结果表明,提出的快速重构算法在保证重构信号性能的基础上,大大减少了重构时间.

References

[1]  Donoho D L. Compressed sensing[J]. IEEE Transaction on Information Theory, 2006, 52(4): 1289-1306.
[2]  Candés E. Compressive sampling[J]. Proceedings of the International Congress of mathematicians, 2006(3): 1433-1452.
[3]  李树涛, 魏丹. 压缩传感综述[J]. 自动化学报, 2009, 35(11): 1369-1377.Li Shutao, Wei Dan. A survey on compressive sensing[J]. ACTA Automatica Sinica, 2009, 35(11): 1369-1377.
[4]  Donoho D L. For most large underdetermined systems of linear equations,the minimal l1 norm solution is also the sparsest solution[J]. Communications on Pure and Applied Mathematics, 2006, 59(6): 797-829.
[5]  Chen S S, Donoho D L, Saunders M A. Atomic decomposition by basis pursuit[J].SIAM Journal on Scientific Computing, 1998, 20(1): 33-61.
[6]  Stephane G. Mallat, Zhang Zhifeng. Matching pursuit in a time-frequency dictionary[J].IEEE Trans Signal Processing, 1993, 41(12): 3397-3415.
[7]  Tropp J, Gilbert A. Signal recovery from random measurements via orthogonal matching pursuit[J]. Transactions on Information Theory, 2007, 53(12): 4655-4666.
[8]  Deanna Needell, Vershynin R. Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit[J]. Foundations of Computational Mathematics, 2009, 9(3): 317-334.
[9]  程云鹏, 张凯院, 徐仲,等. 矩阵论[M] 124页. 西安: 西北工业大学出版社, 2007.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133