不同重构算法对压缩感知重构效果的影响  

Effects of Different Reconstruction Algorithms on Compressed Sensing Reconstruction

作　　者：李瑞明[1] 张烨[1] 杨慧炯[1] 原菊梅[1] 

机构地区：[1]太原工业学院,山西太原030008

出　　处：《太原学院学报（自然科学版）》2016年第4期34-36,共3页Journal of TaiYuan University:Natural Science Edition

基　　金：山西省自然科学基金(2013011018-2)

摘　　要：传统信号处理方法存在采样数据量大、压缩复杂度高的问题,而压缩感知理论可以解决上述问题,因此在模式识别、图像采集以及电能质量信号分析中应用广泛。其中,合适的重构算法可以达到很好的重构精度。文章对压缩感知的基本原理进行了阐述,并对不同恢复算法进行了分析,最后对不同恢复算法的重构效果进行了比较。Compressed sensing can solve such problems as shortage of large volumes of stored data, high complexity of compression in traditional method, so it has been widely used in pattern recognition, image acquisition and power quality analysis. And a suitable reconstruction algorithm can reach high precision. Firstly, this paper reviews its basic principle, and then analyzes different reconstruction algorithms. Lastly this paper compares reconstruction effects of different reconstruction algorithms.

关 键 词：压缩感知 稀疏表示 重构算法 电能质量扰动信号 

分 类 号：S151.9[农业科学—土壤学]