压缩感知中测量矩阵构造综述

doi:10.11772/j.issn.1001-9081.2017.01.0188

摘要/Abstract

摘要： 压缩感知测量矩阵构造方式多样并不断发展，为梳理现有研究成果，掌握测量矩阵发展动态，对压缩感知测量矩阵构造进行系统介绍。首先，针对传统信号采集理论存在的信息冗余问题，阐述了压缩感知理论在信号采集过程中资源利用率高、存储空间小的优势；其次，以压缩感知理论框架为基础，从测量矩阵构造原则、测量矩阵产生方法、测量矩阵结构设计、测量矩阵优化方法四个方面，对压缩感知测量矩阵构造进行分析，讨论了测量矩阵构造过程中不同原则、结构、方法的优势；最后，在总结现有研究成果的基础上，对测量矩阵的发展方向进行了展望。

关键词: 压缩感知, 测量矩阵, 有限等距性质, 信号重构, 信号采集

Abstract: The construction of measurement matrix in compressive sensing varies widely and is on the development constantly. In order to sort out the research results and acquire the development trend of measurement matrix, the process of measurement matrix construction was introduced systematically. Firstly, compared with the traditional signal acquisition theory, the advantages of high resource utilization and small storage space were expounded. Secondly, on the basis of the framework of compressive sensing and focusing on four aspects:the construction principle, the generation method, the structure design of measurement matrix and the optimal method, the construction of measurement matrix in compressive sensing was summarized, and advantages of different principles, generations and structures were introduced in detail. Finally, based on the research results, the development directions of measurement matrix were prospected.

Key words: Compressive Sensing (CS), measurement matrix, Restricted Isometry Property (RIP), signal reconstruction, signal acquisition

中图分类号:

TP301.6

王强, 张培林, 王怀光, 杨望灿, 陈彦龙. 压缩感知中测量矩阵构造综述[J]. 计算机应用, 2017, 37(1): 188-196.

WANG Qiang, ZHANG Peilin, WANG Huaiguang, YANG Wangcan, CHEN Yanlong. Survey on construction of measurement matrices in compressive sensing[J]. Journal of Computer Applications, 2017, 37(1): 188-196.

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