摘要
重构算法是压缩感知的核心技术之一,直接决定着压缩感知能否可以在实际系统中进行应用。为提高压缩感知的重构精度同时缩短处理时间,本文引进加权与矩阵分块技术,与压缩采样匹配追踪(Compressive Sampling Matching Pursuit,Co Sa MP)算法相结合,使原始算法更加完善。仿真结果表明,当稀疏条件同等的情况下进行重构,改进的算法与原始算法相比重构质量有所提高。
Reconstruction algorithm is one of the points of compressed sensing .It determines compressed sensing whether can be applied in the real system.The paper combines compressive sampling matching pursuit （CoSaMP） algorithm with weighted block matrix technology in order to improve the accuracy of compressed sensing reconstruction , shorten the processing time and make the original algorithm more perfect .The paper compares the improved algorithm with the existing algorithms by simulation experi -ments which approve that the new algorithm improves the reconstruction quality under the same sparse condition .
出处
《计算机与现代化》
2015年第5期48-52,共5页
Computer and Modernization
基金
黑龙江省自然科学基金资助项目(201404)
关键词
压缩感知
重构算法
压缩采样匹配追踪
加权
矩阵分块
compressed sensing
reconstruction algorithm
compressive sampling matching pursuit
weighted
block matrix
