电子学报2012，Vol.40Issue(6)：1185-1189,5.DOI:10.3969/j.issn.0372-2112.2012.06.020
基于近似l0范数的稳健稀疏重构算法
Robust Sparse Recovery Based on Approximate l0 Norm
摘要
Abstract
For the problem of recovering sparse vector with noisy measurements, robust approximate l0 norm minimization algorithm is proposed.Firstly, l0 norm is approximately expressed by arctan function. Secondly,the model of sparse recovery in the present of noise is constructed based on approximate l0 norm. Finally, the model is solved by quasi-Newton method to estimate sparse vector.Simulation results show that our algorithm needs fewer measurements and provides the better accuracy than the existing methods.关键词
压缩感知/稀疏重构/基追踪/平滑l0范数Key words
compressed sensing/ sparse recovery/basis pursuit/ smoothed l0 norm分类
信息技术与安全科学引用本文复制引用
王军华,黄知涛,周一宇,王丰华..基于近似l0范数的稳健稀疏重构算法[J].电子学报,2012,40(6):1185-1189,5.基金项目
国家自然科学基金(No.61072120) （No.61072120）
新世纪优秀人才支持计划资助项目(No.SCET) （No.SCET）
