第2讲 压缩感知的关键技术及其研究进展  

Advances in Theory of Compressive Sensing

作　　者：曾理[1] 黄建军[1] 刘亚峰[2] 周彬[1] 

机构地区：[1]解放军理工大学指挥自动化学院研究生2队 [2]中国人民解放军69026部队

出　　处：《军事通信技术》2011年第4期88-94,共7页Journal of Military Communications Technology

基　　金：江苏省自然科学基金资助项目(BK2009059)

摘　　要：压缩感知理论是一种全新的信息处理方式,在多个领域中表现出了极大的生命力和影响力,有着广阔的应用前景。文章分析了压缩感知的基本理论框架,围绕压缩感知的信号稀疏表示方法、测量矩阵构造、信号重构算法三个核心问题,对其最新的研究进展进行了系统总结,并指出了在应用该理论时应该遵循的一些基本原则。Compressive sensing captures and represents compressible signals at a sampling rate significantly below the Nyquist rate. It is an emerging theory of signal acquirement. The theoretical Sramework was reviewed as well as and the three key points of compressive sensing, including sparse representation, measurement matrix construction and signal reconstruction. The latest development of the signal sparse representation, design of measurement matrix and reconstruction algorithm was also introduced with some problems in compressive sensing theory analysed.

关 键 词：压缩感知 稀疏表示 测量矩阵 重构算法 

分 类 号：TN911.7[电子电信—通信与信息系统]