计算机工程与应用2012，Vol.48Issue(29)：157-161,5.DOI:10.3778/j.issn.1002-8331.2012.29.032
一种基于量子粒子群的二次匹配OMP重构算法
Dual matching OMP reconstruction algorithm based on quantum particle swarm
摘要
Abstract
The Orthogonal Matching Pursuit (OMP) algorithm which is based on the idea of greedy iteration is one of the compressed sensing signal reconstruction algorithm. To reduce the OMP computational complexity, quantum particle swarm (QPSO) algorithm which is more powerful in searching for global optimal solution is applied to optimize the matching course of orthogonal matching pursuit algorithm (QPSO-OMP). According to OMP algorithm features the atomic weight secondary matching is introduced to improve the reconstruction accuracy of QPSO-OMP. Simulation results show that the orthogonal matching pursuit algorithm with secondary matching based on the quantum particle swarm algorithm performs better than that based on the particle swarm algorithm in accurate reconstruction probability while with low complexity.关键词
压缩感知/冗余字典/正交匹配追踪算法/量子粒子群算法Key words
compressed sensing/ over-complete dictionary/ orthogonal matching pursuit algorithm/ quantum particle swarm algorithm分类
信息技术与安全科学引用本文复制引用
赵知劲,马春晖..一种基于量子粒子群的二次匹配OMP重构算法[J].计算机工程与应用,2012,48(29):157-161,5.基金项目
国家自然科学基金(No.60872092). （No.60872092）
