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.
出处
《广东工业大学学报》
CAS
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)
关键词
压缩感知
稀疏
不相关
信号分离
compressed sensing
sparse
irrelevance
signal separation
