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ChinhLa_thesis
- SIGNAL RECONSTRUCTIONS FROM LIMITED MEASUREMENTS USING SPARSE-TREE PRIORS
Compression-perception-theory-
- 压缩感知理论及其研究进展,文综述了cs理论框架及关键技术问题，并着重介绍了信号稀疏变换、观测矩阵设计和重构算法三个方面的最新进展，是一篇综述。-Compression perception theory and research progress, cs paper reviews the theoretical framework and key technical issues and focuses on the latest developments signal sparse tran
infocom11-cheng
- In this paper, we propose a novel compressive sensing (CS) based approach for sparse target counting and positioning in wireless sensor networks. While this is not the first work on applying CS to count and localize targets, it is the first t
Sparsity-Inducing-DOA
- 基于稀疏分解的宽带信号DOA估计方法，使用了基于贝叶斯的方法具有良好的估计精度和分辨率-Wideband signal sparse decomposition DOA estimation method based on the use of a method based on Bayesian estimation has good accuracy and resolution
Reference-2
- example we will measure a signal that is sparse in the time domain. We will use a random sensing matrix, and we will solve the recovery problem using the l1-Magic toolbox.