压缩感知是建立在矩阵分析, 统计概率论, 拓扑几何, 优化与运筹学, 泛函分析等基础上的一种
全新的信息获取与处理的理论框架. 它基于信号的可压缩性, 通过低维空间, 低分辨率, 欠Nyquist …

This first chapter formulates the objectives of compressive sensing. It introduces the
standard compressive problem studied throughout the book and reveals its ubiquity in many …

Compressed sensing is an alternative to Shannon/Nyquist sampling for acquiring sparse or
compressible signals. Sparse coding represents a signal as a sparse linear combination of …

Abstract Direction-of-arrival (DOA) estimation refers to the process of retrieving the direction
information of several electromagnetic waves/sources from the outputs of a number of …

We consider the orthogonal matching pursuit (OMP) algorithm for the recovery of a high-
dimensional sparse signal based on a small number of noisy linear measurements. OMP is …

This paper introduces a simple and very general theory of compressive sensing. In this
theory, the sensing mechanism simply selects sensing vectors independently at random …

This paper deals with the computational complexity of conditions which guarantee that the
NP-hard problem of finding the sparsest solution to an underdetermined linear system can …

Orthogonal matching pursuit (OMP) is the canonical greedy algorithm for sparse
approximation. In this paper we demonstrate that the restricted isometry property (RIP) can …

This paper considers compressed sensing and affine rank minimization in both noiseless
and noisy cases and establishes sharp restricted isometry conditions for sparse signal and …

This survey provides a brief introduction to compressed sensing as well as several major
algorithms to solve it and its various applications to communications systems. We firstly …