压缩感知理论及其应用前景

Theory of CS and the Prospect of Its Application

压缩感知理论是近年来提出的一种基于信号稀疏性的新兴采样理论。与通常的数据采样定理不同,该理论提出可以用远远少于传统采样定理所需的采样点数或观测点数恢复出原信号或图像。本文主要阐述了压缩感知中信号的稀疏表示、测量矩阵的设计及信号的重构算法等基本理论,论述了该理论的广阔应用前景。

The theory of compressive sensing（CS）relying on signal sparsity,is a new sampling theory proposed recently.Going against the common wisdom in data acquisition,CS theory asserts that one can recover certain signals and images from far fewer samples or measurements than traditional method use.This paper presents some basic theories of CS,including signal sparse representation,design of measurement matrix and reconstruction algorithm and discusses the bright prospect of its application.