计算机应用研究2017，Vol.34Issue(3)：940-944,5.DOI:10.3969/j.issn.1001-3695.2017.03.070
基于主成分分析的MWC采样数据压缩方法
PCA-based compression method for MWC sampled data
摘要
Abstract
Modulated wideband converter (MWC) was a sub-Nyquist sampling system for sparse multiband analog signals.In the actual design of the MWC,a variety of factors should be considered,such as the hardware implementation and the accurate reconstruction,which might result in high redundancy in the sampled data.This paper deeply analyzed the reasons why the MWC might cause redundancy in the sampled data and the characters of the sampled data for the first time,and proposed a compression method for the sampled data based on the principal component analysis (PCA).The proposed method firstly used PCA transform to concentrate most of the energy of the MWC sampled data on few principal components,and then compressed the sampled data by only retaining,quantizing and encoding these principal components.The experimental results show that the ability of the PCA transform to concentrate the energy of the MWC sampled data outperforms the wavelet transform and the DCT.On the premise of ensuring the reconstruction accuracy higher than 90％,the proposed method can compress the sampled data to less than 1/8 of the original one.关键词
调制带宽转换器/主成分分析/亚奈奎斯特采样/压缩感知Key words
modulated wideband converter/principal component analysis/sub-Nyquist sampling/compressive sensing分类
信息技术与安全科学引用本文复制引用
杜阳,赵辉..基于主成分分析的MWC采样数据压缩方法[J].计算机应用研究,2017,34(3):940-944,5.基金项目
国家自然科学基金资助项目(61271261,61501075) （61271261,61501075）
重庆市教委科学技术研究项目(KJ1400419) （KJ1400419）
重庆邮电大学青年科学基金资助项目(A2015-59) （A2015-59）
