压缩感知原理在盲信号分离中的应用  

The Application of Compressed Sensing in Blind Source Separation

作　　者：王涛文[1] 

机构地区：[1]广东工业大学应用数学学院,广东广州510520

出　　处：《广东工业大学学报》2012年第3期49-53,共5页Journal of Guangdong University of Technology

基　　金：国家自然科学基金资助项目(60974077);广东省自然科学基金资助项目(10251009001000002)

摘　　要：主要阐述了压缩感知的基本原理,介绍了压缩感知的3个基本问题:信号的稀疏表示、稀疏基与测量矩阵的不相关性和信号的重构,分析了它与盲信号分离之间的联系,为解决盲信号分离问题提供了一个新的途径.最后通过具体实验说明它在盲信号分离上的应用.Compressed Sensing has been a new signal sampling theory in recent years, for it overcomes the high rate of sampling defects of traditional Nyquist signal sampling theory, It presented the basic principles of Compressed Sensing, introduced three fundamental questions of Compressed Sensing-the sparseness of signals ,irrelevance between sparse matrix and measurement matrix, and reconstruction of the signals, and analyzed the contact between Compressed Sensing and Blind Source Separation. Then, it offered a new way to solve the problem of Blind Source Separation. Finally, through the experiment it showed its application in Blind Source Separation.

关 键 词：压缩感知 稀疏 不相关 信号分离 

分 类 号：TN912.3[电子电信—通信与信息系统]